Kalliomäki, I.[Ilkka],
Vehtari, A.[Aki],
Lampinen, J.[Jouko],
Shape analysis of concrete aggregates for statistical quality modeling,
MVA(16), No. 3, May 2005, pp. 197-201.
Springer DOI
0505
BibRef
Le Bastard, C.,
Baltazart, V.,
Wang, Y.,
Saillard, J.,
Thin-Pavement Thickness Estimation Using GPR With High-Resolution and
Superresolution Methods,
GeoRS(45), No. 8, August 2007, pp. 2511-2519.
IEEE DOI
0709
BibRef
Bourlier, C.,
Le Bastard, C.,
Baltazart, V.,
Generalization of PILE Method to the EM Scattering From Stratified
Subsurface With Rough Interlayers: Application to the Detection of
Debondings Within Pavement Structure,
GeoRS(53), No. 7, July 2015, pp. 4104-4115.
IEEE DOI
1503
Ground penetrating radar
BibRef
Yamaguchi, T.[Tomoyuki],
Hashimoto, S.[Shuji],
Fast crack detection method for large-size concrete surface images
using percolation-based image processing,
MVA(21), No. 5, August 2010, pp. 797-809.
WWW Link.
1011
BibRef
Earlier:
Improved percolation-based method for crack detection in concrete
surface images,
ICPR08(1-4).
IEEE DOI
0812
BibRef
Clemmensen, L.H.[Line H.],
Hansen, M.E.[Michael E.],
Ersbřll, B.K.[Bjarne K.],
A comparison of dimension reduction methods with application to
multi-spectral images of sand used in concrete,
MVA(21), No. 6, October 2010, pp. 959-968.
WWW Link.
1011
BibRef
Fujita, Y.[Yusuke],
Hamamoto, Y.[Yoshihiko],
A robust automatic crack detection method from noisy concrete surfaces,
MVA(22), No. 2, March 2011, pp. 245-254.
WWW Link.
1103
BibRef
Elunai, R.,
Chandran, V.,
Gallagher, E.,
Asphalt Concrete Surfaces Macrotexture Determination From Still Images,
ITS(12), No. 3, September 2011, pp. 857-869.
IEEE DOI
1109
BibRef
Li, Q.Q.[Qing-Quan],
Zou, Q.[Qin],
Zhang, D.Q.[Da-Qiang],
Mao, Q.Z.[Qing-Zhou],
FoSA: F* Seed-growing Approach for crack-line detection from pavement
images,
IVC(29), No. 12, November 2011, pp. 861-872.
Elsevier DOI
1112
Line detection; Pavement crack; Seed-growing; Dynamic programming
BibRef
Zou, Q.[Qin],
Cao, Y.[Yu],
Li, Q.Q.[Qing-Quan],
Mao, Q.Z.[Qing-Zhou],
Wang, S.[Song],
CrackTree: Automatic crack detection from pavement images,
PRL(33), No. 3, 1 February 2012, pp. 227-238.
Elsevier DOI
1201
Crack detection; Edge detection; Edge grouping; Tensor voting; Shadow removal
BibRef
Suanpaga, W.,
Yoshikazu, K.,
Riding Quality Model for Asphalt Pavement Monitoring Using Phase Array
Type L-band Synthetic Aperture Radar (PALSAR),
RS(2), No. 11, November 2010, pp. 2531-2546.
DOI Link
1203
BibRef
Ndoye, M.,
Barker, A.M.,
Krogmeier, J.V.,
Bullock, D.M.,
A Recursive Multiscale Correlation-Averaging Algorithm for an Automated
Distributed Road-Condition-Monitoring System,
ITS(12), No. 3, September 2011, pp. 795-808.
IEEE DOI
1109
BibRef
Oliveira, H.,
Correia, P.L.,
Automatic Road Crack Detection and Characterization,
ITS(14), No. 1, March 2013, pp. 155-168.
IEEE DOI
1303
BibRef
Fang, H.,
Lin, G.,
Zhang, R.,
The First-Order Symplectic Euler Method for Simulation of GPR Wave
Propagation in Pavement Structure,
GeoRS(51), No. 1, January 2013, pp. 93-98.
IEEE DOI
1301
BibRef
Murthy, S.B.S.,
Varaprasad, G.,
Detection of potholes in autonomous vehicle,
IET-ITS(8), No. 6, September 2014, pp. 543-549.
DOI Link
1411
collision avoidance
BibRef
Shangguan, P.C.[Peng-Cheng],
Al-Qadi, I.L.,
Calibration of FDTD Simulation of GPR Signal for Asphalt Pavement
Compaction Monitoring,
GeoRS(53), No. 3, March 2015, pp. 1538-1548.
IEEE DOI
1412
asphalt
BibRef
Guan, H.[Haiyan],
Li, J.,
Yu, Y.T.[Yong-Tao],
Chapman, M.,
Wang, H.Y.[Han-Yun],
Wang, C.[Cheng],
Zhai, R.F.[Rui-Fang],
Iterative Tensor Voting for Pavement Crack Extraction Using Mobile
Laser Scanning Data,
GeoRS(53), No. 3, March 2015, pp. 1527-1537.
IEEE DOI
1412
crack detection
See also Automated Extraction of Urban Road Facilities Using Mobile Laser Scanning Data.
BibRef
Yi, C.,
Chuang, Y.,
Nian, C.,
Toward Crowdsourcing-Based Road Pavement Monitoring by Mobile Sensing
Technologies,
ITS(16), No. 4, August 2015, pp. 1905-1917.
IEEE DOI
1508
Feature extraction
BibRef
Rajamohan, D.[Deepak],
Gannu, B.[Bhavana],
Rajan, K.S.[Krishnan Sundara],
MAARGHA: A Prototype System for Road Condition and Surface Type
Estimation by Fusing Multi-Sensor Data,
IJGI(4), No. 3, 2015, pp. 1225.
DOI Link
1508
BibRef
Mathavan, S.,
Kamal, K.,
Rahman, M.,
A Review of Three-Dimensional Imaging Technologies for Pavement
Distress Detection and Measurements,
ITS(16), No. 5, October 2015, pp. 2353-2362.
IEEE DOI
1511
Survey, Pavement Analysis. computer vision
BibRef
Quintana, M.,
Torres, J.,
Menéndez, J.M.,
A Simplified Computer Vision System for Road Surface Inspection and
Maintenance,
ITS(17), No. 3, March 2016, pp. 608-619.
IEEE DOI
1603
Cameras
BibRef
Zhang, S.[Su],
Lippitt, C.D.[Christopher D.],
Bogus, S.M.[Susan M.],
Neville, P.R.H.[Paul R. H.],
Characterizing Pavement Surface Distress Conditions with
Hyper-Spatial Resolution Natural Color Aerial Photography,
RS(8), No. 5, 2016, pp. 392.
DOI Link
1606
BibRef
Hoult, N.A.,
Dutton, M.,
Hoag, A.,
Take, W.A.,
Measuring Crack Movement in Reinforced Concrete Using Digital Image
Correlation: Overview and Application to Shear Slip Measurements,
PIEEE(104), No. 8, August 2016, pp. 1561-1574.
IEEE DOI
1608
Area measurement
BibRef
Amhaz, R.[Rabih],
Chambon, S.[Sylvie],
Idier, J.[Jerome],
Baltazart, V.[Vincent],
Automatic Crack Detection on Two-Dimensional Pavement Images: An
Algorithm Based on Minimal Path Selection,
ITS(17), No. 10, October 2016, pp. 2718-2729.
IEEE DOI
1610
BibRef
Earlier:
A new minimal path selection algorithm for automatic crack detection
on pavement images,
ICIP14(788-792)
IEEE DOI
1502
Context
Cost function
BibRef
Ishikawa, T.[Tsuyoshi],
Fujinami, K.[Kaori],
Smartphone-Based Pedestrian's Avoidance Behavior Recognition towards
Opportunistic Road Anomaly Detection,
IJGI(5), No. 10, 2016, pp. 182.
DOI Link
1610
BibRef
Jang, D.W.,
Park, R.H.,
Pothole detection using spatio-temporal saliency,
IET-ITS(10), No. 9, 2016, pp. 605-612.
DOI Link
1609
asphalt
BibRef
Shi, Y.,
Cui, L.,
Qi, Z.,
Meng, F.,
Chen, Z.,
Automatic Road Crack Detection Using Random Structured Forests,
ITS(17), No. 12, December 2016, pp. 3434-3445.
IEEE DOI
1612
Feature extraction
BibRef
Zaini, N.[Nasrullah],
van der Meer, F.[Freek],
van Ruitenbeek, F.[Frank],
de Smeth, B.[Boudewijn],
Amri, F.[Fadli],
Lievens, C.[Caroline],
An Alternative Quality Control Technique for Mineral Chemistry
Analysis of Portland Cement-Grade Limestone Using Shortwave Infrared
Spectroscopy,
RS(8), No. 11, 2016, pp. 950.
DOI Link
1612
BibRef
Zhang, D.[Dejin],
Li, Q.Q.[Qing-Quan],
Chen, Y.[Ying],
Cao, M.[Min],
He, L.[Li],
Zhang, B.L.[Bai-Ling],
An efficient and reliable coarse-to-fine approach for asphalt
pavement crack detection,
IVC(57), No. 1, 2017, pp. 130-146.
Elsevier DOI
1702
Pavement crack detection
BibRef
Casselgren, J.[Johan],
Bodin, U.[Ulf],
Reusable road condition information system for traffic safety and
targeted maintenance,
IET-ITS(11), No. 4, May 2017, pp. 230-238.
DOI Link
1705
BibRef
Lenglet, C.[Céline],
Blanc, J.[Juliette],
Dubroca, S.[Stéphane],
Smart road that warns its network manager when it begins cracking,
IET-ITS(11), No. 3, April 2017, pp. 152-157.
DOI Link
1705
BibRef
González, L.C.,
Moreno, R.,
Escalante, H.J.,
Martínez, F.,
Carlos, M.R.,
Learning Roadway Surface Disruption Patterns Using the Bag of Words
Representation,
ITS(18), No. 11, November 2017, pp. 2916-2928.
IEEE DOI
1711
Accelerometers, Automobiles, Data collection, Roads, Sensors,
Smart phones, Urban areas, Roadway surface disruptions,
accelerometer.
BibRef
Carmon, N.[Nimrod],
Ben-Dor, E.[Eyal],
Mapping Asphaltic Roads' Skid Resistance Using Imaging Spectroscopy,
RS(10), No. 3, 2018, pp. xx-yy.
DOI Link
1804
BibRef
Carlos, M.R.,
Aragón, M.E.,
González, L.C.,
Escalante, H.J.,
Martínez, F.,
Evaluation of Detection Approaches for Road Anomalies Based on
Accelerometer Readings: Addressing Who's Who,
ITS(19), No. 10, October 2018, pp. 3334-3343.
IEEE DOI
1810
Roads, Accelerometers, Sensors, Support vector machines, Proposals,
Acceleration, Accelerometer measurements, mobile sensing,
road anomalies
BibRef
Zhang, Y.,
Chen, C.,
Wu, Q.,
Lu, Q.,
Zhang, S.,
Zhang, G.,
Yang, Y.,
A Kinect-Based Approach for 3D Pavement Surface Reconstruction and
Cracking Recognition,
ITS(19), No. 12, December 2018, pp. 3935-3946.
IEEE DOI
1812
Surface cracks,
Surface reconstruction, Sensors, Image reconstruction,
BibRef
Zhao, S.,
Al-Qadi, I.L.,
Super-Resolution of 3-D GPR Signals to Estimate Thin Asphalt Overlay
Thickness Using the XCMP Method,
GeoRS(57), No. 2, February 2019, pp. 893-901.
IEEE DOI
1901
Signal resolution, Ground penetrating radar, Dielectric constant,
Antennas, Image resolution, Asphalt, Estimation,
thin asphalt overlay
BibRef
Li, Z.Q.[Zhi-Qiang],
Cheng, C.Q.[Cheng-Qi],
Kwan, M.P.[Mei-Po],
Tong, X.C.[Xiao-Chong],
Tian, S.H.[Shao-Hong],
RETRACTION: Identifying Asphalt Pavement Distress Using UAV LiDAR Point Cloud
Data and Random Forest Classification,
IJGI(8), No. 9, 2019, pp. xx-yy.
DOI Link
1909
BibRef
And:
IJGI(8), No. 1, 2019, pp. xx-yy.
DOI Link
1901
BibRef
Feng, H.[Hui],
Xu, G.S.[Guo-Sheng],
Guo, Y.H.[Yan-Hui],
Multi-scale classification network for road crack detection,
IET-ITS(13), No. 2, February 2019, pp. 398-405.
DOI Link
1902
BibRef
Li, H.,
Song, D.,
Liu, Y.,
Li, B.,
Automatic Pavement Crack Detection by Multi-Scale Image Fusion,
ITS(20), No. 6, June 2019, pp. 2025-2036.
IEEE DOI
1906
Training data, Manuals, Feature extraction, Training, Clutter,
Image edge detection, Fuses, Crack detection,
robotic airport runway inspection
BibRef
Kaddah, W.[Wissam],
Elbouz, M.[Marwa],
Ouerhani, Y.[Yousri],
Baltazart, V.[Vincent],
Alfalou, A.[Ayman],
Optimized minimal path selection (OMPS) method for automatic and
unsupervised crack segmentation within two-dimensional pavement images,
VC(35), No. 9, September 2018, pp. 1293-1309.
Springer DOI
1908
BibRef
Tan, Y.M.[Yu-Min],
Li, Y.X.[Yun-Xin],
UAV Photogrammetry-Based 3D Road Distress Detection,
IJGI(8), No. 9, 2019, pp. xx-yy.
DOI Link
1909
BibRef
Fan, R.,
Ozgunalp, U.,
Hosking, B.,
Liu, M.,
Pitas, I.,
Pothole Detection Based on Disparity Transformation and Road Surface
Modeling,
IP(29), No. 1, 2020, pp. 897-908.
IEEE DOI
1910
BibRef
And:
Corrections:
IP(29), 2020, pp. 3091-3091.
IEEE DOI
2002
Pothole detection, road surface modeling.
Roads, Surface treatment,
Surface reconstruction, Detection algorithms, Sea surface,
surface normal
BibRef
Yang, W.W.[Wen-Wei],
Finite element model of concrete material based on CT image
processing technology,
JVCIR(64), 2019, pp. 102631.
Elsevier DOI
1911
CT image, Numerical model, Concrete, Failure process
BibRef
Cheng, L.[Lushan],
Zhang, X.[Xu],
Shen, J.[Jie],
Road surface condition classification using deep learning,
JVCIR(64), 2019, pp. 102638.
Elsevier DOI
1911
Deep learning, Road condition, Activation function,
Image recognition, Intelligent driving
BibRef
Hadavandsiri, Z.[Zahra],
Lichti, D.D.[Derek D.],
Jahraus, A.[Adam],
Jarron, D.[David],
Concrete Preliminary Damage Inspection by Classification of
Terrestrial Laser Scanner Point Clouds through Systematic Threshold
Definition,
IJGI(8), No. 12, 2019, pp. xx-yy.
DOI Link
1912
BibRef
Mohammadi, M.E.[Mohammad Ebrahim],
Wood, R.L.[Richard L.],
Wittich, C.E.[Christine E.],
Non-Temporal Point Cloud Analysis for Surface Damage in Civil
Structures,
IJGI(8), No. 12, 2019, pp. xx-yy.
DOI Link
1912
BibRef
Fei, Y.,
Wang, K.C.P.,
Zhang, A.,
Chen, C.,
Li, J.Q.,
Liu, Y.,
Yang, G.,
Li, B.,
Pixel-Level Cracking Detection on 3D Asphalt Pavement Images Through
Deep-Learning- Based CrackNet-V,
ITS(21), No. 1, January 2020, pp. 273-284.
IEEE DOI
2001
Surface cracks, Asphalt, Libraries,
Feature extraction, Deep learning, Kernel, CrackNet, CrackNet-V,
surface cracks
BibRef
de Blasiis, M.R.[Maria Rosaria],
di Benedetto, A.[Alessandro],
Fiani, M.[Margherita],
Mobile Laser Scanning Data for the Evaluation of Pavement Surface
Distress,
RS(12), No. 6, 2020, pp. xx-yy.
DOI Link
2003
BibRef
Kashiyama, T.[Takehiro],
Sekimoto, Y.[Yoshihide],
Seto, T.[Toshikazu],
Lwin, K.K.[Ko Ko],
Analyzing Road Coverage of Public Vehicles According to Number and
Time Period for Installation of Road Inspection Systems,
IJGI(9), No. 3, 2020, pp. xx-yy.
DOI Link
2004
BibRef
Yang, F.,
Zhang, L.,
Yu, S.,
Prokhorov, D.,
Mei, X.,
Ling, H.,
Feature Pyramid and Hierarchical Boosting Network for Pavement Crack
Detection,
ITS(21), No. 4, April 2020, pp. 1525-1535.
IEEE DOI
2004
Feature extraction, Image edge detection, Deep learning, Boosting,
Task analysis, Semantics, Wavelet transforms,
hierarchical boosting
BibRef
Pu, Z.Y.[Zi-Yuan],
Cui, Z.Y.[Zhi-Yong],
Wang, S.[Shuo],
Li, Q.[Qianmu],
Wang, Y.[Yinhai],
Time-aware gated recurrent unit networks for forecasting road surface
friction using historical data with missing values,
IET-ITS(14), No. 4, April 2020, pp. 213-219.
DOI Link
2004
BibRef
Kaddah, W.[Wissam],
Elbouz, M.[Marwa],
Ouerhani, Y.[Yousri],
Alfalou, A.[Ayman],
Desthieux, M.[Marc],
Automatic darkest filament detection (ADFD): a new algorithm for crack
extraction on two-dimensional pavement images,
VC(36), No. 7, July 2020, pp. 1369-1384.
Springer DOI
2005
BibRef
Meyer, F.J.[Franz J.],
Ajadi, O.A.[Olaniyi A.],
Hoppe, E.J.[Edward J.],
Studying the Applicability of X-Band SAR Data to the Network-Scale
Mapping of Pavement Roughness on US Roads,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link
2005
BibRef
Xiang, X.Z.[Xue-Zhi],
Zhang, Y.Q.[Yu-Qi],
El Saddik, A.[Abdulmotaleb],
Pavement crack detection network based on pyramid structure and
attention mechanism,
IET-IPR(14), No. 8, 19 June 2020, pp. 1580-1586.
DOI Link
2005
BibRef
Zou, L.,
Yi, L.,
Sato, M.,
On the Use of Lateral Wave for the Interlayer Debonding Detecting in
an Asphalt Airport Pavement Using a Multistatic GPR System,
GeoRS(58), No. 6, June 2020, pp. 4215-4224.
IEEE DOI
2005
Asphalt airport pavement, common midpoint (CMP),
ground-penetrating radar (GPR), interlayer debonding detection,
nondestructive inspection
BibRef
Du, Y.,
Liu, C.,
Song, Y.,
Li, Y.,
Shen, Y.,
Rapid Estimation of Road Friction for Anti-Skid Autonomous Driving,
ITS(21), No. 6, June 2020, pp. 2461-2470.
IEEE DOI
2006
Roads, Friction, Resistance, Electrical resistance measurement,
Standards, Autonomous vehicles, Immune system, Autonomous vehicle,
velocity control
BibRef
Rodés, J.P.[Josep Pedret],
Reguero, A.M.[Adriana Martínez],
Pérez-Gracia, V.[Vega],
GPR Spectra for Monitoring Asphalt Pavements,
RS(12), No. 11, 2020, pp. xx-yy.
DOI Link
2006
BibRef
Debroux, N.[Noémie],
Le Guyader, C.[Carole],
Vese, L.A.[Luminita A.],
A Nonlocal Laplacian-Based Model for Bituminous Surfacing Crack
Recovery and its MPI Implementation,
JMIV(62), No. 6-7, July 2020, pp. 1007-1033.
Springer DOI
2007
BibRef
Dhiman, A.,
Klette, R.,
Pothole Detection Using Computer Vision and Learning,
ITS(21), No. 8, August 2020, pp. 3536-3550.
IEEE DOI
2008
Roads, Image reconstruction, Shape,
Accelerometers, Cameras,
deep learning
BibRef
Abdellatif, M.[Mohamed],
Peel, H.[Harriet],
Cohn, A.G.[Anthony G.],
Fuentes, R.[Raul],
Pavement Crack Detection from Hyperspectral Images Using A Novel
Asphalt Crack Index,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link
2009
BibRef
Fan, R.,
Liu, M.,
Road Damage Detection Based on Unsupervised Disparity Map
Segmentation,
ITS(21), No. 11, November 2020, pp. 4906-4911.
IEEE DOI
2011
Roads, Image segmentation, Cameras, Sensors, numerical solution
BibRef
Fan, R.[Rui],
Ozgunalp, U.[Umar],
Wang, Y.[Yuan],
Liu, M.[Ming],
Pitas, I.[Ioannis],
Rethinking Road Surface 3-D Reconstruction and Pothole Detection:
From Perspective Transformation to Disparity Map Segmentation,
Cyber(52), No. 7, July 2022, pp. 5799-5808.
IEEE DOI
2207
Roads, Surface morphology, Sensors, Cameras, Surface reconstruction,
Estimation, Disparity map transformation,
simple linear iterative clustering
BibRef
Mattheuwsen, L.[Lukas],
Vergauwen, M.[Maarten],
Manhole Cover Detection on Rasterized Mobile Mapping Point Cloud Data
Using Transfer Learned Fully Convolutional Neural Networks,
RS(12), No. 22, 2020, pp. xx-yy.
DOI Link
2011
BibRef
Özdemir, O.B.[Okan Bilge],
Soydan, H.[Hilal],
Çetin, Y. .Y.[Yasemin Yardimci],
Düzgün, H.S.[Hafize Sebnem],
Neural Network Based Pavement Condition Assessment with Hyperspectral
Images,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link
2012
BibRef
Mettas, C.[Christodoulos],
Evagorou, E.[Evagoras],
Agapiou, A.[Athos],
Hadjimitsis, D.[Diofantos],
The Use of Colorimeters to Support Remote Sensing Techniques on
Asphalt Pavements,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link
2012
BibRef
Fiorentini, N.[Nicholas],
Maboudi, M.[Mehdi],
Leandri, P.[Pietro],
Losa, M.[Massimo],
Gerke, M.[Markus],
Surface Motion Prediction and Mapping for Road Infrastructures
Management by PS-InSAR Measurements and Machine Learning Algorithms,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link
2012
BibRef
Yu, Y.[Yang],
Rashidi, M.[Maria],
Samali, B.[Bijan],
Yousefi, A.M.[Amir M.],
Wang, W.Q.[Wei-Qiang],
Multi-Image-Feature-Based Hierarchical Concrete Crack Identification
Framework Using Optimized SVM Multi-Classifiers and D-S Fusion
Algorithm for Bridge Structures,
RS(13), No. 2, 2021, pp. xx-yy.
DOI Link
2101
BibRef
Zhang, K.,
Zhang, Y.,
Cheng, H.D.,
CrackGAN: Pavement Crack Detection Using Partially Accurate Ground
Truths Based on Generative Adversarial Learning,
ITS(22), No. 2, February 2021, pp. 1306-1319.
IEEE DOI
2102
Training, Feature extraction, Generative adversarial networks,
Image segmentation, Generators, Semantics,
partially accurate ground truths
BibRef
Liu, Z.[Zhen],
Wu, W.X.[Wen-Xiu],
Gu, X.Y.[Xing-Yu],
Li, S.W.[Shu-Wei],
Wang, L.[Lutai],
Zhang, T.J.[Tian-Jie],
Application of Combining YOLO Models and 3D GPR Images in Road
Detection and Maintenance,
RS(13), No. 6, 2021, pp. xx-yy.
DOI Link
2104
BibRef
Pan, J.,
Sun, M.,
Wang, Y.,
Le Bastard, C.,
Baltazart, V.,
Time-Delay Estimation by a Modified Orthogonal Matching Pursuit
Method for Rough Pavement,
GeoRS(59), No. 4, April 2021, pp. 2973-2981.
IEEE DOI
2104
Ground penetrating radar, Matching pursuit algorithms,
Estimation, Frequency measurement, Media, Data models,
time-delay estimation (TDE)
BibRef
Dérobert, X.[Xavier],
Baltazart, V.[Vincent],
Simonin, J.M.[Jean-Michel],
Todkar, S.S.[Shreedhar Savant],
Norgeot, C.[Christophe],
Hui, H.Y.[Ho-Yan],
GPR Monitoring of Artificial Debonded Pavement Structures throughout
Its Life Cycle during Accelerated Pavement Testing,
RS(13), No. 8, 2021, pp. xx-yy.
DOI Link
2104
BibRef
Shen, R.Q.[Rui-Qing],
Zhao, Y.H.[Yong-Hui],
Hu, S.F.[Shu-Fan],
Li, B.[Bo],
Bi, W.[Wenda],
Reverse-Time Migration Imaging of Ground-Penetrating Radar in NDT of
Reinforced Concrete Structures,
RS(13), No. 10, 2021, pp. xx-yy.
DOI Link
2105
BibRef
Xu, J.C.[Jun-Cai],
Zhang, J.K.[Jing-Kui],
Sun, W.G.[Wei-Gang],
Recognition of the Typical Distress in Concrete Pavement Based on GPR
and 1D-CNN,
RS(13), No. 12, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Diamanti, N.[Nectaria],
Annan, A.P.[A. Peter],
Jackson, S.R.[Steven R.],
Klazinga, D.[Dylan],
A GPR-Based Pavement Density Profiler: Operating Principles and
Applications,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link
2107
BibRef
Bhattacharya, G.[Gaurab],
Mandal, B.[Bappaditya],
Puhan, N.B.[Niladri B.],
Interleaved Deep Artifacts-Aware Attention Mechanism for Concrete
Structural Defect Classification,
IP(30), 2021, pp. 6957-6969.
IEEE DOI
2108
Feature extraction, Concrete, Aggregates,
Inspection, Monitoring, Meteorology, Fine-grained dense module,
multi-target multi-class classification
BibRef
Bhattacharya, G.[Gaurab],
Mandal, B.[Bappaditya],
Puhan, N.B.[Niladri B.],
Multi-Deformation Aware Attention Learning for Concrete Structural
Defect Classification,
CirSysVideo(31), No. 9, September 2021, pp. 3707-3713.
IEEE DOI
2109
Feature extraction, Corrosion, Bars, Tensile stress, Data mining,
Distance measurement,
multi-target multi-class classification
BibRef
Tankeu, B.T.[Bachir Tchana],
Baltazart, V.[Vincent],
Wang, Y.[Yide],
Guilbert, D.[David],
PUMA Applied to Time Delay Estimation for Processing GPR Data over
Debonded Pavement Structures,
RS(13), No. 17, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Rasol, M.[Mezgeen],
Schmidt, F.[Franziska],
Ientile, S.[Silvia],
Adelaide, L.[Lucas],
Nedjar, B.[Boumediene],
Kane, M.[Malal],
Chevalier, C.[Christophe],
Progress and Monitoring Opportunities of Skid Resistance in Road
Transport: A Critical Review and Road Sensors,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Song, Y.Z.[Yong-Ze],
Wu, P.[Peng],
Gilmore, D.[Daniel],
Li, Q.[Qindong],
A Spatial Heterogeneity-Based Segmentation Model for Analyzing Road
Deterioration Network Data in Multi-Scale Infrastructure Systems,
ITS(22), No. 11, November 2021, pp. 7073-7083.
IEEE DOI
2112
Roads, Monitoring, Australia, Data models, Data analysis,
Spatial databases, Image segmentation,
spatial analysis
BibRef
Fan, R.[Rui],
Wang, H.[Hengli],
Wang, Y.[Yuan],
Liu, M.[Ming],
Pitas, I.[Ioannis],
Graph Attention Layer Evolves Semantic Segmentation for Road Pothole
Detection: A Benchmark and Algorithms,
IP(30), 2021, pp. 8144-8154.
IEEE DOI
2110
Roads, Image segmentation, Semantics,
Convolutional neural networks, Feature extraction,
graph neural network
BibRef
Cao, Q.Q.[Qing-Qing],
Al-Qadi, I.L.[Imad L.],
Effect of Moisture Content on Calculated Dielectric Properties of
Asphalt Concrete Pavements from Ground-Penetrating Radar Measurements,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link
2201
BibRef
Chen, C.[Cheng],
Chandra, S.[Sindhu],
Han, Y.F.[Yu-Fan],
Seo, H.[Hyungjoon],
Deep Learning-Based Thermal Image Analysis for Pavement Defect
Detection and Classification Considering Complex Pavement Conditions,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link
2201
BibRef
Wei, Z.X.[Zi-Xian],
SUN, T.[Tao],
Wu, Y.H.[Yu-Hao],
Zhou, L.Q.[Li-Qing],
Ruan, X.L.[Xiao-Li],
Pavement crack detection using non-local theory and iterative
sampling,
IET-IPR(16), No. 3, 2022, pp. 869-877.
DOI Link
2202
BibRef
Fan, L.[Lili],
Zhao, H.W.[Hong-Wei],
Li, Y.[Ying],
Li, S.[Shen],
Zhou, R.[Rui],
Chu, W.B.[Wen-Bo],
RAO-UNet: a residual attention and octave UNet for road crack
detection via balance loss,
IET-ITS(16), No. 3, 2022, pp. 332-343.
DOI Link
2202
BibRef
Sun, M.[Mingsi],
Zhao, H.W.[Hong-Wei],
Li, J.[Jiao],
Road crack detection network under noise based on feature pyramid
structure with feature enhancement (road crack detection under noise),
IET-IPR(16), No. 3, 2022, pp. 809-822.
DOI Link
2202
BibRef
Simonin, J.M.[Jean-Michel],
Piau, J.M.[Jean-Michel],
Le-Boursicault, V.[Vinciane],
Freitas, M.[Murilo],
Orthogonal Set of Indicators for the Assessment of Flexible Pavement
Stiffness from Deflection Monitoring: Theoretical Formalism and
Numerical Study,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link
2202
BibRef
Guo, S.[Shili],
Xu, Z.W.[Zhi-Wei],
Li, X.Z.[Xiu-Zhong],
Zhu, P.M.[Pei-Min],
Detection and Characterization of Cracks in Highway Pavement with the
Amplitude Variation of GPR Diffracted Waves: Insights from Forward
Modeling and Field Data,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link
2202
BibRef
Zhang, L.L.[Liang-Liang],
Wang, L.[Lin],
Yang, B.[Bo],
Niu, S.[Sijie],
Han, Y.M.[Ya-Min],
Oh, S.K.[Sung-Kwun],
Rapid construction of 4D high-quality microstructural image for
cement hydration using partial information registration,
PR(124), 2022, pp. 108471.
Elsevier DOI
2203
Cement hydration, Rapid image construction, Image registration,
Particle swarm optimization, Microstructural temporal image sequences
BibRef
Zhou, Q.[Qiang],
Qu, Z.[Zhong],
Ju, F.R.[Fang-Rong],
A multi-scale learning method with dilated convolutional network for
concrete surface cracks detection,
IET-IPR(16), No. 5, 2022, pp. 1389-1402.
DOI Link
2203
BibRef
Yu, Y.T.[Yong-Tao],
Guan, H.Y.[Hai-Yan],
Li, D.[Dilong],
Zhang, Y.J.[Yong-Jun],
Jin, S.H.[Sheng-Hua],
Yu, C.H.[Chang-Hui],
CCapFPN: A Context-Augmented Capsule Feature Pyramid Network for
Pavement Crack Detection,
ITS(23), No. 4, April 2022, pp. 3324-3335.
IEEE DOI
2204
Feature extraction, Deep learning, Image edge detection,
Task analysis, Monitoring, Neurons, Fuses, Crack detection, deep learning
BibRef
Chen, Y.[Yihan],
Gu, X.Y.[Xing-Yu],
Liu, Z.[Zhen],
Liang, J.[Jia],
A Fast Inference Vision Transformer for Automatic Pavement Image
Classification and Its Visual Interpretation Method,
RS(14), No. 8, 2022, pp. xx-yy.
DOI Link
2205
BibRef
Ling, J.Y.[Jian-Yu],
Qian, R.Y.[Rong-Yi],
Shang, K.[Ke],
Guo, L.Y.[Lin-Yan],
Zhao, Y.[Yu],
Liu, D.Y.[Dong-Yi],
Research on the Dynamic Monitoring Technology of Road Subgrades with
Time-Lapse Full-Coverage 3D Ground Penetrating Radar (GPR),
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link
2205
BibRef
Daraghmi, Y.A.[Yousef-Awwad],
Wu, T.H.[Tsung-Hsiang],
Ik, T.U.[Tsě-Uí],
Crowdsourcing-Based Road Surface Evaluation and Indexing,
ITS(23), No. 5, May 2022, pp. 4164-4175.
IEEE DOI
2205
Roads, Rough surfaces, Surface roughness, Monitoring, Smart phones,
Vibrations, Standards, Crowdsourcing, road roughness,
power spectral density
BibRef
Ahmed, A.[Adeel],
Ashfaque, M.[Moeez],
Ulhaq, M.U.[Muhammad Uzair],
Mathavan, S.[Senthan],
Kamal, K.[Khurram],
Rahman, M.[Mujib],
Pothole 3D Reconstruction With a Novel Imaging System and Structure
From Motion Techniques,
ITS(23), No. 5, May 2022, pp. 4685-4694.
IEEE DOI
2205
Cameras, Roads, Image reconstruction,
Surface reconstruction, Measurement by laser beam,
metrology
BibRef
Chen, Z.P.[Zhi-Peng],
Li, Q.Q.[Qing-Quan],
Xue, W.X.[Wei-Xin],
Zhang, D.[Dejin],
Xiong, S.[Siting],
Yin, Y.[Yu],
Lv, S.[Shiwang],
Rapid Inspection of Large Concrete Floor Flatness Using Wheeled Robot
with Aided-INS,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link
2205
BibRef
Yuan, G.[Genji],
Li, J.B.[Jian-Bo],
Meng, X.L.[Xiang-Long],
Li, Y.[Yinong],
CurSeg: A pavement crack detector based on a deep hierarchical
feature learning segmentation framework,
IET-ITS(16), No. 6, 2022, pp. 782-799.
DOI Link
2205
BibRef
Park, M.J.[Min Jae],
Kim, J.[Jihyung],
Jeong, S.[Sanggi],
Jang, A.[Arum],
Bae, J.[Jaehoon],
Ju, Y.K.[Young K.],
Machine Learning-Based Concrete Crack Depth Prediction Using Thermal
Images Taken under Daylight Conditions,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link
2205
BibRef
Schladitz, K.[Katja],
Methods for segmenting cracks in 3d images of concrete:
A comparison based on semi-synthetic images,
PR(129), 2022, pp. 108747.
Elsevier DOI
2206
Computed tomography, Fractional Brownian surface,
3d segmentation, Crack detection, Machine learning, Deep learning
BibRef
Khadka, R.[Rajiv],
Acharya, M.[Mahesh],
LaBrier, D.[Daniel],
Mashal, M.[Mustafa],
Visualization of Macroscopic Structure of Ultra-high Performance
Concrete Based on X-ray Computed Tomography Using Immersive
Environments,
VAMR22(I:20-33).
Springer DOI
2206
BibRef
Vassilev, V.[Vessen],
Road Surface Recognition at mm-Wavelengths Using a Polarimetric Radar,
ITS(23), No. 7, July 2022, pp. 6985-6990.
IEEE DOI
2207
Surface roughness, Rough surfaces, Ice, Coherence,
Scattering parameters, Radar, Radar polarimetry, Radar polarimetry,
target entropy
BibRef
Vassilev, V.[Vessen],
Road Surface Characterization Using a 77-81 GHz Polarimetric Radar,
ITS(25), No. 9, September 2024, pp. 12829-12834.
IEEE DOI
2409
Surface roughness, Rough surfaces, Entropy, Scattering, Roads, Radar,
Radar polarimetry, Radar polarimetry, ice,
target entropy
BibRef
Tang, W.H.[Wen-Hao],
Huang, S.[Sheng],
Zhao, Q.M.[Qi-Ming],
Li, R.[Ren],
Huangfu, L.[Luwen],
An Iteratively Optimized Patch Label Inference Network for Automatic
Pavement Distress Detection,
ITS(23), No. 7, July 2022, pp. 8652-8661.
IEEE DOI
2207
Diseases, Task analysis, Roads, Object detection, Feature extraction,
Image segmentation, Image resolution,
object localization
BibRef
Sun, M.[Meng],
Pan, J.J.[Jing-Jing],
Wang, Y.[Yide],
Zhang, X.F.[Xiao-Fei],
Xiao, X.T.[Xiao-Ting],
Fauchard, C.[Cyrille],
Bastard, C.L.[Cédric Le],
Time-Delay Estimation by Enhanced Orthogonal Matching Pursuit Method
for Thin Asphalt Pavement With Similar Permittivity,
ITS(23), No. 7, July 2022, pp. 8940-8948.
IEEE DOI
2207
Asphalt, Permittivity, Matching pursuit algorithms, Estimation,
Media, Matrix decomposition, Task analysis, Pavement survey,
orthogonal matching pursuit (OMP)
BibRef
Ji, K.[Kun],
Zhang, Z.H.[Zhen-Hai],
Yu, J.L.[Jia-Le],
Dang, J.W.[Jian-Wu],
A deep learning-based method for pixel-level crack detection on
concrete bridges,
IET-IPR(16), No. 10, 2022, pp. 2609-2622.
DOI Link
2207
BibRef
Zhang, B.[Bin],
Zhao, H.[Hua],
Tan, C.J.[Cheng-Jun],
OBrien, E.J.[Eugene J.],
Fitzgerald, P.C.[Paul C.],
Kim, C.W.[Chul-Woo],
Laboratory Investigation on Detecting Bridge Scour Using the Indirect
Measurement from a Passing Vehicle,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Zhang, Y.[Yi],
Fan, J.F.[Jun-Fu],
Zhang, M.Z.[Meng-Zhen],
Shi, Z.W.[Zong-Wen],
Liu, R.F.[Ru-Fei],
Guo, B.[Bing],
A Recurrent Adaptive Network: Balanced Learning for Road Crack
Segmentation with High-Resolution Images,
RS(14), No. 14, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Souriou, D.[David],
Kadkhodazadeh, S.[Sima],
Dérobert, X.[Xavier],
Guilbert, D.[David],
Ihamouten, A.[Amine],
Experimental Parametric Study of a Functional-Magnetic Material
Designed for the Monitoring of Corrosion in Reinforced Concrete
Structures,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Feng, H.F.[Hui-Fang],
Li, W.[Wen],
Luo, Z.P.[Zhi-Peng],
Chen, Y.P.[Yi-Ping],
Fatholahi, S.N.[Sarah Narges],
Cheng, M.[Ming],
Wang, C.[Cheng],
Junior, J.M.[José Marcato],
Li, J.[Jonathan],
GCN-Based Pavement Crack Detection Using Mobile LiDAR Point Clouds,
ITS(23), No. 8, August 2022, pp. 11052-11061.
IEEE DOI
2208
Roads, Feature extraction, Learning systems, Laser radar, Inspection,
Shape, Pavement crack detection, MLS point clouds, semi-supervised, GCN
BibRef
Feng, H.F.[Hui-Fang],
Li, W.[Wen],
Ma, L.F.[Ling-Fei],
Chen, Y.P.[Yi-Ping],
Guan, H.Y.[Hai-Yan],
Yu, Y.T.[Yong-Tao],
Junior, J.M.[José Marcato],
Li, J.[Jonathan],
Crack-U2Net: Multiscale Feature Learning Network for Pavement Crack
Detection from Large-Scale MLS Point Clouds,
ITS(25), No. 11, November 2024, pp. 17952-17964.
IEEE DOI
2411
Feature extraction, Point cloud compression, Accuracy, Roads,
Training data, Deep learning, Representation learning, data augmentation
BibRef
Zhu, W.X.[Wen-Xuan],
Tan, W.K.[Wei-Kan],
Ma, L.F.[Ling-Fei],
Zhang, D.D.[De-Dong],
Li, J.[Jonathan],
Chapman, M.A.[Michael A.],
A Capsnets Approach to Pavement Crack Detection Using Mobile Laser
Scannning Point Clouds,
ISPRS21(B1-2021: 39-44).
DOI Link
2201
BibRef
Dong, H.W.[Hong-Wen],
Song, K.C.[Ke-Chen],
Wang, Y.Y.[Yan-Yan],
Yan, Y.H.[Yun-Hui],
Jiang, P.[Peng],
Automatic Inspection and Evaluation System for Pavement Distress,
ITS(23), No. 8, August 2022, pp. 12377-12387.
IEEE DOI
2208
Image segmentation, Feature extraction, Inspection,
Convolutional neural networks, Roads, Costs, Training,
guidance attention
BibRef
Wang, D.Y.[Dan-Yu],
Liu, Z.[Zhen],
Gu, X.Y.[Xing-Yu],
Wu, W.X.[Wen-Xiu],
Chen, Y.H.[Yi-Han],
Wang, L.T.[Lu-Tai],
Automatic Detection of Pothole Distress in Asphalt Pavement Using
Improved Convolutional Neural Networks,
RS(14), No. 16, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Elseicy, A.[Ahmed],
Alonso-Díaz, A.[Alex],
Solla, M.[Mercedes],
Rasol, M.[Mezgeen],
Santos-Assunçao, S.[Sonia],
Combined Use of GPR and Other NDTs for Road Pavement Assessment: An
Overview,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link
2209
BibRef
Chen, H.[Hui],
Jin, W.[Wuyin],
Xuan, J.[Jiamin],
Data Analysis for Dynamics of Cooperative Bridge-Vehicle System
Considering Pavement Roughness and Separation,
ITS(23), No. 9, September 2022, pp. 16820-16832.
IEEE DOI
2209
Tires, Vehicle dynamics, Bridges, Nonlinear dynamical systems, Roads,
Numerical models, Analytical models,
radial nonlinear multi-spring-damper tire (RNMST)
BibRef
Qu, Z.[Zhong],
Wang, C.Y.[Cai-Yun],
Wang, S.Y.[Shi-Yan],
Ju, F.R.[Fang-Rong],
A Method of Hierarchical Feature Fusion and Connected Attention
Architecture for Pavement Crack Detection,
ITS(23), No. 9, September 2022, pp. 16038-16047.
IEEE DOI
2209
Convolution, Feature extraction, Kernel, Roads, Deep learning,
Image edge detection, dilated convolution
BibRef
Ma, Y.[Yuan],
Chen, F.[Feng],
Ma, T.[Tao],
Huang, X.M.[Xiao-Ming],
Zhang, Y.[Yang],
Intelligent Compaction: An Improved Quality Monitoring and Control of
Asphalt Pavement Construction Technology,
ITS(23), No. 9, September 2022, pp. 14875-14882.
IEEE DOI
2209
Compaction, Asphalt, Indexes, Harmonic analysis, Vibrations, Rocks,
Roads, Compaction uniformity, evaluation index of compaction,
semivariogram
BibRef
Zhang, Y.J.[Yu-Jia],
Wu, J.X.[Jun-Xian],
Li, Q.Z.[Qian-Zhong],
Zhao, X.G.[Xiao-Guang],
Tan, M.[Min],
Beyond Crack: Fine-Grained Pavement Defect Segmentation Using
Three-Stream Neural Networks,
ITS(23), No. 9, September 2022, pp. 14820-14832.
IEEE DOI
2209
Image segmentation, Task analysis, Shape, Inspection, Roads, Lighting,
Maintenance engineering, Fine-grained defect segmentation,
pavement inspection
BibRef
Liao, J.H.[Jiang-Hai],
Yue, Y.H.[Yuan-Hao],
Zhang, D.[Dejin],
Tu, W.[Wei],
Cao, R.[Rui],
Zou, Q.[Qin],
Li, Q.Q.[Qing-Quan],
Automatic Tunnel Crack Inspection Using an Efficient Mobile Imaging
Module and a Lightweight CNN,
ITS(23), No. 9, September 2022, pp. 15190-15203.
IEEE DOI
2209
Inspection, Cameras, Imaging, Charge coupled devices, Sensors,
Feature extraction, Surface emitting lasers, Tunnel inspection,
spatial constraint
BibRef
Bridgelall, R.[Raj],
Characterizing Ride Quality With a Composite Roughness Index,
ITS(23), No. 9, September 2022, pp. 15288-15297.
IEEE DOI
2209
Indexes, Rough surfaces, Smart phones, Roads, ISO Standards,
Data collection, Standards, International roughness index,
vehicle design
BibRef
Liu, C.Q.[Chuan-Qi],
Zhu, C.G.[Cheng-Guang],
Xia, X.[Xuan],
Zhao, J.K.[Jian-Kang],
Long, H.H.[Hai-Hui],
FFEDN: Feature Fusion Encoder Decoder Network for Crack Detection,
ITS(23), No. 9, September 2022, pp. 15546-15557.
IEEE DOI
2209
Feature extraction, Decoding, Shape, Semantics, Interference,
Task analysis, Image edge detection, Crack detection,
shape semantic prior
BibRef
Bhattacharya, G.[Gaurab],
Puhan, N.B.,
Mandal, B.[Bappaditya],
Kernelized dynamic convolution routing in spatial and channel
interaction for attentive concrete defect recognition,
SP:IC(108), 2022, pp. 116818.
Elsevier DOI
2209
Kernel salient feature encoder, Spatial-channel attention,
Concrete structural defect, Convolutional neural network,
Multi-target multi-class classification
BibRef
Miwa, T.[Takashi],
Nakazawa, Y.[Yuri],
Nondestructive Evaluation of Localized Rebar Corrosion in Concrete
Using Vibro-Radar Based on Pulse Doppler Imaging,
RS(14), No. 18, 2022, pp. xx-yy.
DOI Link
2209
BibRef
Li, N.[Nansha],
Wu, R.B.[Ren-Biao],
Li, H.F.[Hai-Feng],
Wang, H.C.[Huai-Chao],
Gui, Z.C.[Zhong-Cheng],
Song, D.Z.[De-Zhen],
MV-GPRNet: Multi-View Subsurface Defect Detection Network for Airport
Runway Inspection Based on GPR,
RS(14), No. 18, 2022, pp. xx-yy.
DOI Link
2209
BibRef
Zhao, L.[Langyue],
Wu, Y.[Yiquan],
Luo, X.D.[Xu-Dong],
Yuan, Y.[Yubin],
Automatic Defect Detection of Pavement Diseases,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link
2210
BibRef
Sun, X.Z.[Xin-Zi],
Xie, Y.C.[Yuan-Chang],
Jiang, L.M.[Li-Ming],
Cao, Y.[Yu],
Liu, B.[Benyuan],
DMA-Net: DeepLab With Multi-Scale Attention for Pavement Crack
Segmentation,
ITS(23), No. 10, October 2022, pp. 18392-18403.
IEEE DOI
2210
Image segmentation, Convolution, Semantics, Roads, Decoding,
Feature extraction, Pavement crack segmentation,
multi-scale attention
BibRef
Ganguly, B.[Biswarup],
Dey, D.[Debangshu],
Munshi, S.[Sugata],
An Unsupervised Learning Approach for Road Anomaly Segmentation Using
RGB-D Sensor for Advanced Driver Assistance System,
ITS(23), No. 10, October 2022, pp. 19042-19053.
IEEE DOI
2210
Roads, Image segmentation, Anomaly detection,
Unsupervised learning, Vehicles, Real-time systems
BibRef
Zhou, Q.[Qiang],
Qu, Z.[Zhong],
Wang, S.Y.[Shi-Yan],
Bao, K.H.[Kang-Hua],
A Method of Potentially Promising Network for Crack Detection With
Enhanced Convolution and Dynamic Feature Fusion,
ITS(23), No. 10, October 2022, pp. 18736-18745.
IEEE DOI
2210
Convolution, Feature extraction, Strips, Kernel, Task analysis,
Deep learning, Surface treatment, Crack detection,
dynamic feature fusion
BibRef
Fang, J.[Jie],
Yang, C.[Chen],
Shi, Y.[Yuetian],
Wang, N.[Nan],
Zhao, Y.[Yang],
External Attention Based TransUNet and Label Expansion Strategy for
Crack Detection,
ITS(23), No. 10, October 2022, pp. 19054-19063.
IEEE DOI
2210
Feature extraction, Transformers, Roads, Mathematical models,
Deep learning, Convolution, Semantics, Crack detection, TransUNet,
label expansion
BibRef
Abdelraouf, A.[Amr],
Abdel-Aty, M.[Mohamed],
Wu, Y.[Yina],
Using Vision Transformers for Spatial-Context-Aware Rain and Road
Surface Condition Detection on Freeways,
ITS(23), No. 10, October 2022, pp. 18546-18556.
IEEE DOI
2210
Rain, Meteorology, Roads, Transformers, Feature extraction,
Task analysis, Rain detection, road surface condition detection,
sequence-to-sequence detection
BibRef
Kim, J.W.[Jae-Wook],
Kim, E.[Eunkyung],
Kim, D.[Dongwan],
A Black Ice Detection Method Based on 1-Dimensional CNN Using mmWave
Sensor Backscattering,
RS(14), No. 20, 2022, pp. xx-yy.
DOI Link
2211
BibRef
Sekar, A.[Aravindkumar],
Perumal, V.[Varalakshmi],
CFC-GAN: Forecasting Road Surface Crack Using Forecasted Crack
Generative Adversarial Network,
ITS(23), No. 11, November 2022, pp. 21378-21391.
IEEE DOI
2212
Roads, Generative adversarial networks, Predictive models, Faces,
Surface cracks, Forecasting, Aging, road crack forecasting
BibRef
Dong, Q.[Qiao],
Chen, X.Q.[Xue-Qin],
Dong, S.[Shi],
Ni, F.[Fujian],
Data Analysis in Pavement Engineering: An Overview,
ITS(23), No. 11, November 2022, pp. 22020-22039.
IEEE DOI
2212
Mathematical models, Predictive models, Data analysis, Data models,
Indexes, Optical sensors, Feature extraction, Pavement, supervised learning
BibRef
Ma, X.Y.[Xian-Yong],
Dong, Z.J.[Ze-Jiao],
Dong, Y.K.[Yong-Kang],
Toward Asphalt Pavement Health Monitoring With Built-In Sensors: A
Novel Application to Real-Time Modulus Evaluation,
ITS(23), No. 11, November 2022, pp. 22040-22052.
IEEE DOI
2212
Sensors, Asphalt, Real-time systems, Monitoring, Mechanical sensors,
Layout, Strain, Asphalt pavement, modulus evaluation,
multi-layered medium
BibRef
Deng, Y.[Yong],
Shi, X.M.[Xian-Ming],
An Accurate, Reproducible and Robust Model to Predict the Rutting of
Asphalt Pavement: Neural Networks Coupled With Particle Swarm
Optimization,
ITS(23), No. 11, November 2022, pp. 22063-22072.
IEEE DOI
2212
Predictive models, Correlation, Computational modeling,
Data models, Artificial neural networks, Analytical models, robustness
BibRef
Song, Y.[Yang],
Wang, Y.Z.D.[Yi-Zhuang David],
Hu, X.B.[Xian-Biao],
Liu, J.[Jenny],
An Efficient and Explainable Ensemble Learning Model for Asphalt
Pavement Condition Prediction Based on LTPP Dataset,
ITS(23), No. 11, November 2022, pp. 22084-22093.
IEEE DOI
2212
Predictive models, Rough surfaces, Data models, Training,
Radio frequency, Asphalt, Indexes, Asphalt pavement,
long-term pavement performance (LTPP)
BibRef
Yao, L.Y.[Lin-Yi],
Leng, Z.[Zhen],
Jiang, J.[Jiwang],
Ni, F.[Fujian],
Large-Scale Maintenance and Rehabilitation Optimization for
Multi-Lane Highway Asphalt Pavement: A Reinforcement Learning
Approach,
ITS(23), No. 11, November 2022, pp. 22094-22105.
IEEE DOI
2212
Optimization, Costs, Maintenance engineering, Roads,
Biological system modeling, Uncertainty, Indexes,
managerial flexibility
BibRef
Luo, X.[Xue],
Wang, H.[Hang],
Deng, Y.[Yong],
Li, H.[Hui],
Automatic Inverse Analysis of Asphalt Pavement Field Aging Based on
System Identification,
ITS(23), No. 11, November 2022, pp. 22106-22115.
IEEE DOI
2212
Aging, Asphalt, Mathematical models, Predictive models,
Kinetic theory, Analytical models, Databases, Inverse problems,
asphalt pavement
BibRef
Tan, Y.Q.[Yi-Qiu],
Liang, Z.[Zundong],
Xu, H.[Huining],
Xing, C.[Chao],
Research on Rutting Deformation Monitoring Method Based on
Intelligent Aggregate,
ITS(23), No. 11, November 2022, pp. 22116-22126.
IEEE DOI
2212
Aggregates, Asphalt, Strain, Monitoring, Compaction, Loading,
Correlation, Intelligent aggregate (IA), asphalt pavement,
attitude signal law
BibRef
Zhao, J.[Jingnan],
Wang, H.[Hao],
Chen, Y.H.[Yu-Heng],
Huang, M.F.[Ming-Fang],
Detection of Road Surface Anomaly Using Distributed Fiber Optic
Sensing,
ITS(23), No. 11, November 2022, pp. 22127-22134.
IEEE DOI
2212
Roads, Sensors, Support vector machines, Feature extraction,
Optical imaging, Convolutional neural networks, Transforms, DFOS,
CNN
BibRef
Han, C.J.[Cheng-Jia],
Ma, T.[Tao],
Huyan, J.[Ju],
Huang, X.M.[Xiao-Ming],
Zhang, Y.N.[Yan-Ning],
CrackW-Net: A Novel Pavement Crack Image Segmentation Convolutional
Neural Network,
ITS(23), No. 11, November 2022, pp. 22135-22144.
IEEE DOI
2212
Image segmentation, Convolution, Convolutional neural networks,
Roads, Feature extraction, Task analysis, Neural networks,
semantic segmentation
BibRef
Liu, F.Y.[Fang-Yu],
Liu, J.[Jian],
Wang, L.[Linbing],
Asphalt Pavement Crack Detection Based on Convolutional Neural
Network and Infrared Thermography,
ITS(23), No. 11, November 2022, pp. 22145-22155.
IEEE DOI
2212
Computational modeling, Image segmentation, Complexity theory,
Cameras, Measurement, Convolutional neural networks, Asphalt,
asphalt pavement
BibRef
Hou, Y.[Yue],
Liu, S.[Shuo],
Cao, D.D.[Dan-Dan],
Peng, B.[Bo],
Liu, Z.[Zhuo],
Sun, W.J.[Wen-Juan],
Chen, N.[Ning],
A Deep Learning Method for Pavement Crack Identification Based on
Limited Field Images,
ITS(23), No. 11, November 2022, pp. 22156-22165.
IEEE DOI
2212
Convolutional neural networks, Generative adversarial networks,
Image processing, Data models, Training, Image edge detection,
pavement
BibRef
Ma, D.[Duo],
Fang, H.Y.[Hong-Yuan],
Wang, N.[Niannian],
Zhang, C.[Chao],
Dong, J.X.[Jia-Xiu],
Hu, H.[Haobang],
Automatic Detection and Counting System for Pavement Cracks Based on
PCGAN and YOLO-MF,
ITS(23), No. 11, November 2022, pp. 22166-22178.
IEEE DOI
2212
Autonomous aerial vehicles, Graphics processing units,
Generative adversarial networks, Roads, Real-time systems,
crack tracking and counting
BibRef
Yao, H.[Hui],
Liu, Y.[Yanhao],
Li, X.[Xin],
You, Z.[Zhanping],
Feng, Y.[Yu],
Lu, W.W.[Wei-Wei],
A Detection Method for Pavement Cracks Combining Object Detection and
Attention Mechanism,
ITS(23), No. 11, November 2022, pp. 22179-22189.
IEEE DOI
2212
Feature extraction, Object detection, Neural networks, Roads,
Computational modeling, Image segmentation,
attention mechanism
BibRef
Liu, Z.[Zhen],
Gu, X.Y.[Xing-Yu],
Yang, H.[Hailu],
Wang, L.[Lutai],
Chen, Y.[Yihan],
Wang, D.Y.[Dan-Yu],
Novel YOLOv3 Model With Structure and Hyperparameter Optimization for
Detection of Pavement Concealed Cracks in GPR Images,
ITS(23), No. 11, November 2022, pp. 22258-22268.
IEEE DOI
2212
Roads, Feature extraction, Training, Optimization, Bayes methods,
Antenna arrays, Ground penetrating radar, concealed cracks,
Bayesian optimization
BibRef
Liang, X.M.[Xing-Min],
Yu, X.[Xin],
Chen, C.[Chen],
Jin, Y.[Yong],
Huang, J.[Jiandong],
Automatic Classification of Pavement Distress Using 3D
Ground-Penetrating Radar and Deep Convolutional Neural Network,
ITS(23), No. 11, November 2022, pp. 22269-22277.
IEEE DOI
2212
Convolutional neural networks, Radar, Feature extraction,
Radar imaging, Maintenance engineering, Roads, Pavement distress,
automatic classification
BibRef
del Río-Barral, P.[Pablo],
Soilán, M.[Mario],
González-Collazo, S.M.[Silvia María],
Arias, P.[Pedro],
Pavement Crack Detection and Clustering via Region-Growing Algorithm
from 3D MLS Point Clouds,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Kadkhodazadeh, S.[Sima],
Ihamouten, A.[Amine],
Souriou, D.[David],
Dérobert, X.[Xavier],
Guilbert, D.[David],
Parametric Study to Evaluate the Geometry and Coupling Effect on the
Efficiency of a Novel FMM Tool Embedded in Cover Concrete for
Corrosion Monitoring,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Shokri, P.[Parnia],
Shahbazi, M.[Mozhdeh],
Nielsen, J.[John],
Semantic Segmentation and 3D Reconstruction of Concrete Cracks,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Wang, Y.Z.[Yuan-Zheng],
Qin, H.[Hui],
Miao, F.[Feng],
A Multi-Path Encoder Network for GPR Data Inversion to Improve Defect
Detection in Reinforced Concrete,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Wang, X.[Xue],
Shen, S.H.[Shi-Hui],
Huang, H.[Hai],
Zhang, W.G.[Wei-Guang],
In-Situ Modulus Determination Using Dispersion Curves Developed From
the Deflection-Time History Data,
ITS(23), No. 11, November 2022, pp. 22053-22062.
IEEE DOI
2212
Dispersion, Surface waves, Asphalt, Sensors, History, Receivers,
Transportation, In-situ modulus, nondestructive testing,
falling weight deflectometer (FWD)
BibRef
Hu, Q.F.[Qing-Feng],
Wang, P.[Peng],
Li, S.M.[Shi-Ming],
Liu, W.K.[Wen-Kai],
Li, Y.F.[Yi-Fan],
Lu, W.Q.[Wei-Qiang],
Kou, Y.C.[Ying-Chao],
Wei, F.P.[Fu-Peng],
He, P.P.[Pei-Pei],
Yu, A.[Anzhu],
Research on Intelligent Crack Detection in a Deep-Cut Canal Slope in
the Chinese South-North Water Transfer Project,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Guo, J.M.[Jing-Ming],
Markoni, H.[Herleeyandi],
Efficient and Adaptable Patch-Based Crack Detection,
ITS(23), No. 11, November 2022, pp. 21885-21896.
IEEE DOI
2212
Decoding, Feature extraction, Transformers, Roads, Detectors,
Convolution, Inspection, Patch-based processing, CNN, Linformer,
demanded controller
BibRef
König, J.[Jacob],
Jenkins, M.D.[Mark David],
Mannion, M.[Mike],
Barrie, P.[Peter],
Morison, G.[Gordon],
Weakly-Supervised Surface Crack Segmentation by Generating
Pseudo-Labels Using Localization With a Classifier and Thresholding,
ITS(23), No. 12, December 2022, pp. 24083-24094.
IEEE DOI
2212
Image segmentation, Surface cracks, Location awareness, Training,
Surface morphology, Standards, Convolutional neural networks,
neural networks
BibRef
Zeng, M.Y.[Meng-Yuan],
Zhao, H.[Hongduo],
Gao, D.[Dachen],
Bian, Z.[Zeying],
Wu, D.F.[Di-Fei],
Reconstruction of Vehicle-Induced Vibration on Concrete Pavement
Using Distributed Fiber Optic,
ITS(23), No. 12, December 2022, pp. 24305-24317.
IEEE DOI
2212
Vibrations, Monitoring, Vibration measurement, Optical sensors,
Optical variables measurement, Loading, Power cables, Pavement,
accelerated pavement test
BibRef
Chen, X.[Xiao],
Zhang, X.F.[Xian-Feng],
Li, J.[Jonathan],
Ren, M.[Miao],
Zhou, B.[Bo],
A New Method for Automated Monitoring of Road Pavement Aging
Conditions Based on Recurrent Neural Network,
ITS(23), No. 12, December 2022, pp. 24510-24523.
IEEE DOI
2212
Aging, Roads, Monitoring, Asphalt, Satellites, Deep learning, Indexes,
Remote sensing, recurrent neural network, multispectral imagery
BibRef
Li, Y.[Yishun],
Liu, C.L.[Cheng-Long],
Gao, Q.[Qian],
Wu, D.F.[Di-Fei],
Li, F.[Feng],
Du, Y.C.[Yu-Chuan],
ConTrack Distress Dataset: A Continuous Observation for Pavement
Deterioration Spatio-Temporal Analysis,
ITS(23), No. 12, December 2022, pp. 25004-25017.
IEEE DOI
2212
Roads, Feature extraction, Rough surfaces, Indexes, Deep learning,
Asphalt, Aggregates, Pavement distress, deep learning,
pavement deterioration analysis
BibRef
Chen, N.[Ning],
Xu, Z.J.[Zi-Jin],
Liu, Z.[Zhuo],
Chen, Y.[Yihan],
Miao, Y.H.[Ying-Hao],
Li, Q.H.[Qiu-Han],
Hou, Y.[Yue],
Wang, L.B.[Lin-Bing],
Data Augmentation and Intelligent Recognition in Pavement Texture
Using a Deep Learning,
ITS(23), No. 12, December 2022, pp. 25427-25436.
IEEE DOI
2212
Deep learning, Training, Roads, Feature extraction, Random forests,
Generative adversarial networks, Data models, Data augmentation,
autonomous driving
BibRef
Su, B.[Binyi],
Zhang, H.[Hua],
Wu, Z.H.[Zhao-Hui],
Zhou, Z.[Zhong],
FSRDD: An Efficient Few-Shot Detector for Rare City Road Damage
Detection,
ITS(23), No. 12, December 2022, pp. 24379-24388.
IEEE DOI
2212
Roads, Detectors, Feature extraction, Prototypes, Proposals, Training,
Measurement, Road damage, deep learning, few-shot detection, fine-tuning
BibRef
Tian, Y.L.[Yao-Lin],
Wan, X.[Xue],
Wu, A.[Aodi],
Zhao, G.Y.[Guang-Yuan],
Scene Aware Semantic Crack Segmentation from Oblique Drone Imagery,
ICPR22(585-592)
IEEE DOI
2212
Degradation, Image segmentation, Roads, Semantics, Buildings,
Feature extraction, Computational efficiency
BibRef
Al Duhayyim, M.[Mesfer],
Malibari, A.A.[Areej A.],
Alharbi, A.[Abdullah],
Afef, K.[Kallekh],
Yafoz, A.[Ayman],
Alsini, R.[Raed],
Alghushairy, O.[Omar],
Mohsen, H.[Heba],
Road Damage Detection Using the Hunger Games Search with Elman Neural
Network on High-Resolution Remote Sensing Images,
RS(14), No. 24, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Jafari, F.[Faezeh],
Dorafshan, S.[Sattar],
Comparison between Supervised and Unsupervised Learning for
Autonomous Delamination Detection Using Impact Echo,
RS(14), No. 24, 2022, pp. xx-yy.
DOI Link
2212
detect subsurface delamination in reinforced concrete bridge decks.
BibRef
Li, K.[Kai],
Wang, B.[Bo],
Tian, Y.J.[Ying-Jie],
Qi, Z.Q.[Zhi-Quan],
Fast and Accurate Road Crack Detection Based on Adaptive
Cost-Sensitive Loss Function,
Cyber(53), No. 2, February 2023, pp. 1051-1062.
IEEE DOI
2301
Roads, Training, Costs, Image edge detection, Training data,
Sampling methods, Adaptation models, Crack detection,
weighted cross-entropy (WCE)
BibRef
Gagliardi, V.[Valerio],
Tosti, F.[Fabio],
Ciampoli, L.B.[Luca Bianchini],
Battagliere, M.L.[Maria Libera],
d'Amato, L.[Luigi],
Alani, A.M.[Amir M.],
Benedetto, A.[Andrea],
Satellite Remote Sensing and Non-Destructive Testing Methods for
Transport Infrastructure Monitoring:
Advances, Challenges and Perspectives,
RS(15), No. 2, 2023, pp. xx-yy.
DOI Link
2301
More general monitoring.
BibRef
Yu, S.[Shuai],
Shen, S.H.[Shi-Hui],
Compaction Prediction for Asphalt Mixtures Using Wireless Sensor and
Machine Learning Algorithms,
ITS(24), No. 1, January 2023, pp. 778-786.
IEEE DOI
2301
Compaction, Asphalt, Support vector machines,
Machine learning algorithms, Sensors, Mathematical models,
sensing technology
BibRef
Liu, H.J.[Hui-Jun],
Yang, C.H.[Chun-Hua],
Li, A.[Ao],
Huang, S.[Sheng],
Feng, X.[Xin],
Ruan, Z.M.[Zhi-Min],
Ge, Y.X.[Yong-Xin],
Deep Domain Adaptation for Pavement Crack Detection,
ITS(24), No. 2, February 2023, pp. 1669-1681.
IEEE DOI
2302
Feature extraction, Annotations, Training, Support vector machines,
Roads, Diseases, Neural networks, Pavement crack detection,
convolutional neural network
BibRef
Lin, C.M.[Chun-Mian],
Tian, D.X.[Da-Xin],
Duan, X.T.[Xu-Ting],
Zhou, J.S.[Jian-Shan],
Zhao, D.Z.[De-Zong],
Cao, D.[Dongpu],
DA-RDD: Toward Domain Adaptive Road Damage Detection Across Different
Countries,
ITS(24), No. 3, March 2023, pp. 3091-3103.
IEEE DOI
2303
Roads, Feature extraction, Training, Surface cracks,
Convolutional neural networks, Annotations, Adaptation models,
intelligent transportation systems
BibRef
Deng, L.[Lu],
Zhang, A.[An],
Guo, J.J.[Jing-Jing],
Liu, Y.[Yingkai],
An Integrated Method for Road Crack Segmentation and Surface Feature
Quantification under Complex Backgrounds,
RS(15), No. 6, 2023, pp. 1530.
DOI Link
2304
BibRef
Han, C.J.[Cheng-Jia],
Ma, T.[Tao],
Gu, L.[Linhao],
Cao, J.[Jinde],
Shi, X.[Xinli],
Huang, W.[Wei],
Tong, Z.[Zheng],
Asphalt Pavement Health Prediction Based on Improved Transformer
Network,
ITS(24), No. 4, April 2023, pp. 4482-4493.
IEEE DOI
2304
Transformers, Time series analysis, Roads, Tensors, Asphalt,
Predictive models, Monitoring, Asphalt pavement, health prediction,
artificial neural network
BibRef
Wang, Y.Y.[Yan-Yan],
Niu, M.H.[Meng-Hui],
Song, K.[Kechen],
Jiang, P.[Peng],
Yan, Y.H.[Yun-Hui],
Normal-Knowledge-Based Pavement Defect Segmentation Using
Relevance-Aware and Cross-Reasoning Mechanisms,
ITS(24), No. 4, April 2023, pp. 4413-4427.
IEEE DOI
2304
Image reconstruction, Transformers, Image segmentation,
Feature extraction, Training, Semantics, Inspection,
context-aware abnormal distillation
BibRef
Song, W.D.[Wei-Dong],
Zhang, Z.[Zaiyan],
Zhang, B.[Bing],
Jia, G.H.[Guo-Hui],
Zhu, H.B.[Hong-Bo],
Zhang, J.[Jinhe],
ISTD-PDS7: A Benchmark Dataset for Multi-Type Pavement Distress
Segmentation from CCD Images in Complex Scenarios,
RS(15), No. 7, 2023, pp. 1750.
DOI Link
2304
BibRef
Wu, J.Y.[Jia-Yi],
Shi, Y.F.[Yu-Feng],
Wang, H.L.[He-Long],
Wen, Y.J.[Ya-Juan],
Du, Y.W.[Yi-Wei],
Surface Defect Detection of Nanjing City Wall Based on UAV Oblique
Photogrammetry and TLS,
RS(15), No. 8, 2023, pp. 2089.
DOI Link
2305
BibRef
Zhang, C.[Chong],
Chen, Y.[Yang],
Tang, L.[Luliang],
Chu, X.[Xu],
Li, C.K.[Chao-Kui],
CTCD-Net: A Cross-Layer Transmission Network for Tiny Road Crack
Detection,
RS(15), No. 8, 2023, pp. 2185.
DOI Link
2305
BibRef
Huang, S.[Sheng],
Tang, W.H.[Wen-Hao],
Huang, G.X.[Gui-Xin],
Huangfu, L.[Luwen],
Yang, D.[Dan],
Weakly Supervised Patch Label Inference Networks for Efficient
Pavement Distress Detection and Recognition in the Wild,
ITS(24), No. 5, May 2023, pp. 5216-5228.
IEEE DOI
2305
Image recognition, Image classification, Task analysis,
Deep learning, Training, Roads, Inspection, Pavement image analysis,
weakly supervised learning
BibRef
Fan, L.[Lili],
Cao, D.[Dongpu],
Zeng, C.X.[Chang-Xian],
Li, B.[Bai],
Li, Y.J.[Yun-Jie],
Wang, F.Y.[Fei-Yue],
Cognitive-Based Crack Detection for Road Maintenance: An Integrated
System in Cyber-Physical-Social Systems,
SMCS(53), No. 6, June 2023, pp. 3485-3500.
IEEE DOI
2305
Roads, Maintenance engineering, Metaverse, Visualization,
Real-time systems, Monitoring, Safety, Brain inspired,
visual cognition
BibRef
Fares, A.[Ali],
Zayed, T.[Tarek],
Industry- and Academic-Based Trends in Pavement Roughness Inspection
Technologies over the Past Five Decades: A Critical Review,
RS(15), No. 11, 2023, pp. 2941.
DOI Link
2306
BibRef
Plati, C.[Christina],
Georgouli, K.[Konstantina],
Loizos, A.[Andreas],
Using NDT Data to Assess the Effect of Pavement Thickness Variability
on Ride Quality,
RS(15), No. 12, 2023, pp. xx-yy.
DOI Link
2307
BibRef
Guo, N.N.[Nan-Ning],
You, L.Y.[Ling-Yun],
Long, Z.[Zhengwu],
Lv, S.T.[Song-Tao],
Diab, A.[Aboelkasim],
Computationally-Affordable Unsupervised Machine Learning Algorithm to
Identify the Level of Distress Severity in Pavement Functional
Performance,
ITS(24), No. 7, July 2023, pp. 7342-7356.
IEEE DOI
2307
Preventive maintenance, Seals, Indexes, Unsupervised learning,
Slurries, Roads, Feature extraction, Unsupervised machine learning,
preventive maintenance strategies
BibRef
Cao, T.[Ting],
Wang, Y.H.[Yu-Hang],
Liu, S.[Sheng],
Pavement Crack Detection Based on 3D Edge Representation and Data
Communication With Digital Twins,
ITS(24), No. 7, July 2023, pp. 7697-7706.
IEEE DOI
2307
Digital twins, Solid modeling, Image edge detection, Data models,
Feature extraction, Data communication, Digital twins,
fractional differential
BibRef
Hijji, M.[Mohammad],
Iqbal, R.[Rahat],
Pandey, A.K.[Anup Kumar],
Doctor, F.[Faiyaz],
Karyotis, C.[Charalampos],
Rajeh, W.[Wahid],
Alshehri, A.[Ali],
Aradah, F.[Fahad],
6G Connected Vehicle Framework to Support Intelligent Road
Maintenance Using Deep Learning Data Fusion,
ITS(24), No. 7, July 2023, pp. 7726-7735.
IEEE DOI
2307
Roads, Maintenance engineering, Data models,
Computational modeling, 6G mobile communication, Training,
intelligent transportation systems
BibRef
Cai, S.[Sudong],
Wakaki, R.[Ryosuke],
Nobuhara, S.[Shohei],
Nishino, K.[Ko],
RGB Road Scene Material Segmentation,
IVC(145), 2024, pp. 104970.
Elsevier DOI
2405
BibRef
Earlier:
ACCV22(II:256-272).
Springer DOI
2307
RGB road scene material segmentation,
Self-attention mechanism, Multi-level feature fusion
BibRef
Khan, M. .A.M.[Md. Al-Masrur],
Harseno, R.W.[Regidestyoko Wasistha],
Kee, S.H.[Seong-Hoon],
Nahid, A.A.[Abdullah-Al],
Development of AI- and Robotics-Assisted Automated
Pavement-Crack-Evaluation System,
RS(15), No. 14, 2023, pp. 3573.
DOI Link
2307
BibRef
Gagarin, N.[Nicolas],
Goulias, D.[Dimitrios],
Mekemson, J.[James],
Condition Rating of Bridge Decks with Fuzzy Sets Modeling for SF-GPR
Surveys,
RS(15), No. 14, 2023, pp. 3631.
DOI Link
2307
BibRef
Djenouri, Y.[Youcef],
Belhadi, A.[Asma],
Houssein, E.H.[Essam H.],
Srivastava, G.[Gautam],
Lin, J.C.W.[Jerry Chun-Wei],
Intelligent Graph Convolutional Neural Network for Road Crack
Detection,
ITS(24), No. 8, August 2023, pp. 8475-8482.
IEEE DOI
2308
Roads, Feature extraction, Convolutional neural networks,
Anomaly detection, Visualization, Training, Behavioral sciences,
SIFT extractor
BibRef
Jiang, W.[Wei],
Li, P.F.[Peng-Fei],
Sha, A.[Aimin],
Li, Y.P.[Yu-Peng],
Yuan, D.D.[Dong-Dong],
Xiao, J.J.[Jing-Jing],
Xing, C.W.[Cheng-Wei],
Research on Pavement Traffic Load State Perception Based on the
Piezoelectric Effect,
ITS(24), No. 8, August 2023, pp. 8264-8278.
IEEE DOI
2308
Sensors, Temperature sensors, Roads, Telecommunication traffic,
Temperature measurement, Axles, Piezoelectric devices, perception accuracy
BibRef
Workman, R.[Robin],
Wong, P.[Patrick],
Wright, A.[Alex],
Wang, Z.[Zhao],
Prediction of Unpaved Road Conditions Using High-Resolution Optical
Satellite Imagery and Machine Learning,
RS(15), No. 16, 2023, pp. 3985.
DOI Link
2309
BibRef
Gao, Z.[Zhi],
Zhao, X.[Xuhui],
Cao, M.[Min],
Li, Z.[Ziyao],
Liu, K.C.[Kang-Cheng],
Chen, B.M.[Ben M.],
Synergizing Low Rank Representation and Deep Learning for Automatic
Pavement Crack Detection,
ITS(24), No. 10, October 2023, pp. 10676-10690.
IEEE DOI
2310
BibRef
Siddiqui, I.[Ifrah],
Mazhar, S.[Suleman],
Hassan, N.[Naufil],
Sultani, W.[Waqas],
Fine-Grained Road Quality Monitoring Using Deep Learning,
ITS(24), No. 10, October 2023, pp. 10691-10701.
IEEE DOI
2310
BibRef
Ren, R.Q.[Rui-Qi],
Shi, P.X.[Pei-Xin],
Jia, P.J.[Peng-Jiao],
Xu, X.Y.[Xiang-Yang],
A Semi-Supervised Learning Approach for Pixel-Level Pavement Anomaly
Detection,
ITS(24), No. 9, September 2023, pp. 10099-10107.
IEEE DOI
2310
BibRef
Liu, H.J.[Hua-Jun],
Yang, J.[Jing],
Miao, X.Y.[Xiang-Yu],
Mertz, C.[Christoph],
Kong, H.[Hui],
CrackFormer Network for Pavement Crack Segmentation,
ITS(24), No. 9, September 2023, pp. 9240-9252.
IEEE DOI
2310
BibRef
Liu, Z.[Zhen],
Yang, Q.F.[Qi-Feng],
Gu, X.Y.[Xing-Yu],
Assessment of Pavement Structural Conditions and Remaining Life
Combining Accelerated Pavement Testing and Ground-Penetrating Radar,
RS(15), No. 18, 2023, pp. 4620.
DOI Link
2310
BibRef
Liang, Z.D.[Zun-Dong],
Xing, C.[Chao],
Xu, H.N.[Hui-Ning],
Tan, Y.Q.[Yi-Qiu],
Qiu, T.[Tairui],
Chai, B.[Bo],
Li, J.[Jilu],
Liu, T.[Tianci],
Asphalt Pavement Compaction and Vehicle Speed Monitoring Using
Intelligent Aggregate,
ITS(24), No. 9, September 2023, pp. 10177-10185.
IEEE DOI
2310
BibRef
Xu, C.[Chuan],
Zhang, Q.[Qi],
Mei, L.[Liye],
Chang, X.F.[Xiu-Feng],
Ye, Z.[Zhaoyi],
Wang, J.J.[Jun-Jian],
Ye, L.[Lang],
Yang, W.[Wei],
Cross-Attention-Guided Feature Alignment Network for Road Crack
Detection,
IJGI(12), No. 9, 2023, pp. 382.
DOI Link
2310
BibRef
Jiang, S.[Shuo],
Strout, Z.[Zach],
He, B.[Bin],
Peng, D.[Daiyan],
Shull, P.B.[Peter B.],
Lo, B.P.L.[Benny P. L.],
Dual Stream Meta Learning for Road Surface Classification and Riding
Event Detection on Shared Bikes,
SMCS(53), No. 11, November 2023, pp. 7188-7200.
IEEE DOI
2310
BibRef
Yang, L.[Lei],
Huang, H.[Hanyun],
Kong, S.Y.[Shu-Yi],
Liu, Y.H.[Yan-Hong],
Yu, H.[Hongnian],
PAF-Net: A Progressive and Adaptive Fusion Network for Pavement Crack
Segmentation,
ITS(24), No. 11, November 2023, pp. 12686-12700.
IEEE DOI
2311
BibRef
Tian, L.[Lin],
Li, Q.Q.[Qing-Quan],
He, L.[Li],
Zhang, D.[Dejin],
Image-Range Stitching and Semantic-Based Crack Detection Methods for
Tunnel Inspection Vehicles,
RS(15), No. 21, 2023, pp. 5158.
DOI Link
2311
BibRef
Hadrian, A.[Adva],
Vainshtein, R.[Roman],
Shapira, B.[Bracha],
Rokach, L.[Lior],
DeepCAN: Hybrid Method for Road Type Classification Using Vehicle
Sensor Data for Smart Autonomous Mobility,
ITS(24), No. 11, November 2023, pp. 11756-11772.
IEEE DOI
2311
BibRef
Zhang, T.J.[Tian-Jie],
Wang, D.L.[Dong-Lei],
Lu, Y.[Yang],
ECSNet: An Accelerated Real-Time Image Segmentation CNN Architecture
for Pavement Crack Detection,
ITS(24), No. 12, December 2023, pp. 15105-15112.
IEEE DOI
2312
BibRef
Xu, Z.C.[Zheng-Chao],
Dai, Z.[Zhe],
Sun, Z.Y.[Zhao-Yun],
Li, W.[Wei],
Dong, S.[Shi],
Pavement Image Enhancement in Pixel-Wise Based on Multi-Level
Semantic Information,
ITS(24), No. 12, December 2023, pp. 15077-15091.
IEEE DOI
2312
BibRef
Xu, Z.J.[Zi-Jin],
Yu, X.[Xin],
Liu, Z.[Zhuo],
Zhang, S.[Song],
Sun, Q.[Qinxia],
Chen, N.[Ning],
Lv, H.T.[Hao-Tian],
Wang, D.W.[Da-Wei],
Hou, Y.[Yue],
Safety Monitoring of Transportation Infrastructure Foundation:
Intelligent Recognition of Subgrade Distresses Based on B-Scan GPR
Images,
ITS(24), No. 12, December 2023, pp. 15468-15477.
IEEE DOI
2312
BibRef
Aghayan-Mashhady, N.[Nima],
Amirkhani, A.[Abdollah],
Road damage detection with bounding box and generative adversarial
networks based augmentation methods,
IET-IPR(18), No. 1, 2024, pp. 154-174.
DOI Link Code:
WWW Link.
2401
convolutional neural nets, image annotation, object detection, road vehicles
BibRef
Wu, Y.[Yanwen],
Hong, M.J.[Ming-Jian],
Li, A.[Ao],
Huang, S.[Sheng],
Liu, H.J.[Hui-Jun],
Ge, Y.X.[Yong-Xin],
Self-Supervised Adversarial Learning for Domain Adaptation of
Pavement Distress Classification,
ITS(25), No. 2, February 2024, pp. 1966-1977.
IEEE DOI
2402
Feature extraction, Task analysis, Self-supervised learning,
Adaptation models, Training, Generators, Data models,
discriminative information
BibRef
Li, K.[Kai],
Yang, J.[Jie],
Ma, S.W.[Si-Wei],
Wang, B.[Bo],
Wang, S.S.[Shan-She],
Tian, Y.J.[Ying-Jie],
Qi, Z.Q.[Zhi-Quan],
Rethinking Lightweight Convolutional Neural Networks for Efficient
and High-Quality Pavement Crack Detection,
ITS(25), No. 1, January 2024, pp. 237-250.
IEEE DOI
2402
Performance evaluation, Deconvolution, Databases, Source coding,
Roads, Decoding, Convolutional neural networks, Crack detection,
feature up-sampling
BibRef
Liu, Y.C.[Yu-Chen],
Liu, F.[Fang],
Liu, W.[Wei],
Huang, Y.C.[Yu-Cheng],
Pavement Distress Detection Using Street View Images Captured via
Action Camera,
ITS(25), No. 1, January 2024, pp. 738-747.
IEEE DOI
2402
Feature extraction, Roads, Computational modeling,
Object detection, Cameras, Task analysis, Neck, Pavement distress,
transfer learning
BibRef
Zhang, H.Y.[Hao-Yuan],
Chen, N.[Ning],
Li, M.[Mei],
Mao, S.J.[Shan-Jun],
The Crack Diffusion Model: An Innovative Diffusion-Based Method for
Pavement Crack Detection,
RS(16), No. 6, 2024, pp. 986.
DOI Link
2403
BibRef
Baiocchi, V.[Valerio],
Zhang, X.F.[Xian-Feng],
Mei, A.[Alessandro],
Road Extraction and Distress Assessment by Spaceborne, Airborne, and
Terrestrial Platforms,
RS(16), No. 8, 2024, pp. 1416.
DOI Link
2405
BibRef
Zhang, B.[Bei],
Cheng, H.Y.[Hao-Yuan],
Zhong, Y.H.[Yan-Hui],
Chi, J.[Jing],
Shen, G.Y.[Guo-Yin],
Yang, Z.X.[Zhao-Xu],
Li, X.L.[Xiao-Long],
Xu, S.J.[Sheng-Jie],
Real-Time Detection of Voids in Asphalt Pavement Based on
Swin-Transformer-Improved YOLOv5,
ITS(25), No. 3, March 2024, pp. 2615-2626.
IEEE DOI
2405
Asphalt, Numerical models, Real-time systems, Radar,
Ground penetrating radar, Radar imaging, Radar detection,
real-time detection
BibRef
Wang, Y.[Yong],
He, Z.L.[Zheng-Long],
Zeng, X.Q.[Xiang-Qiang],
Zeng, J.C.[Jun-Cheng],
Cen, Z.X.[Zong-Xi],
Qiu, L.Y.[Lu-Yang],
Xu, X.W.[Xiao-Wei],
Zhuo, Q.X.[Qun-Xiong],
GGMNet: Pavement-Crack Detection Based on Global Context Awareness
and Multi-Scale Fusion,
RS(16), No. 10, 2024, pp. 1797.
DOI Link
2405
BibRef
Duan, Z.X.[Ze-Xian],
Liu, J.H.[Jia-Hang],
Ling, X.P.[Xin-Peng],
Zhang, J.L.[Jin-Long],
Liu, Z.H.[Zhi-Heng],
ERNet: A Rapid Road Crack Detection Method Using Low-Altitude UAV
Remote Sensing Images,
RS(16), No. 10, 2024, pp. 1741.
DOI Link
2405
BibRef
Cai, W.Y.[Wen-Yuan],
Song, A.[Andi],
Du, Y.C.[Yu-Chuan],
Liu, C.L.[Cheng-Long],
Wu, D.F.[Di-Fei],
Li, F.[Feng],
Fine-Grained Pavement Performance Prediction Based on Causal-Temporal
Graph Convolution Networks,
ITS(25), No. 5, May 2024, pp. 4606-4619.
IEEE DOI Code:
WWW Link.
2405
Predictive models, Time series analysis, Roads,
Maintenance engineering, Entropy, Couplings,
temporal dependence
BibRef
Cheng, X.[Xu],
He, T.[Tian],
Shi, F.[Fan],
Zhao, M.[Meng],
Liu, X.[Xiufeng],
Chen, S.Y.[Sheng-Yong],
Selective Feature Fusion and Irregular-Aware Network for Pavement
Crack Detection,
ITS(25), No. 5, May 2024, pp. 3445-3456.
IEEE DOI
2405
Feature extraction, Image edge detection, Roads, Lighting, Fuses,
Deep learning, Computer architecture, Deep learning,
selective feature fusion
BibRef
Arvanitis, G.[Gerasimos],
Stagakis, N.[Nikolaos],
Zacharaki, E.I.[Evangelia I.],
Moustakas, K.[Konstantinos],
Cooperative Saliency-Based Pothole Detection and AR Rendering for
Increased Situational Awareness,
ITS(25), No. 5, May 2024, pp. 3588-3604.
IEEE DOI
2405
Roads, Point cloud compression, Laser radar, Cameras,
Rendering (computer graphics), Real-time systems, driver's safety
BibRef
Bai, S.[Suli],
Yang, L.[Lei],
Liu, Y.H.[Yan-Hong],
Yu, H.[Hongnian],
DMF-Net: A Dual-Encoding Multi-Scale Fusion Network for Pavement
Crack Detection,
ITS(25), No. 6, June 2024, pp. 5981-5996.
IEEE DOI Code:
WWW Link.
2406
Feature extraction, Transformers, Image segmentation,
Task analysis, Roads, Convolutional neural networks, Deep learning,
multi-scale feature learning
BibRef
Li, C.[Chong],
Fan, Z.[Zhun],
Chen, Y.[Ying],
Lin, H.B.[Hui-Biao],
Moretti, L.[Laura],
Loprencipe, G.[Giuseppe],
Sheng, W.H.[Wei-Hua],
Wang, K.C.P.[Kelvin C. P.],
CrackCLF: Automatic Pavement Crack Detection Based on Closed-Loop
Feedback,
ITS(25), No. 6, June 2024, pp. 5965-5980.
IEEE DOI
2406
Feature extraction, Neural networks, Image segmentation,
Generative adversarial networks, Roads, Task analysis, Training,
closed-loop feedback
BibRef
Wang, A.[Aidi],
Lang, H.[Hong],
Chen, Z.[Zhen],
Peng, Y.C.[Yi-Chuan],
Ding, S.[Shuo],
Lu, J.J.[Jian John],
The Two-Step Method of Pavement Pothole and Raveling Detection and
Segmentation Based on Deep Learning,
ITS(25), No. 6, June 2024, pp. 5402-5417.
IEEE DOI
2406
Feature extraction, Asphalt, Object detection, Roads, Deep learning,
Semantic segmentation, Pothole and raveling,
deep learning
BibRef
Wang, J.[Jin],
Si, Q.[Qi],
Song, Z.[Ziang],
Wang, D.[Duo],
Yao, H.[Hui],
3D Geometry Modeling and Safety Compliance Assessment of In-Service
Roads Using Massive LiDAR Point Clouds,
ITS(25), No. 6, June 2024, pp. 4977-4986.
IEEE DOI
2406
Roads, Point cloud compression, Safety, Laser radar, Geometry,
Road safety, Road geometry, LiDAR point clouds, road safety, deep learning
BibRef
Zheng, W.W.[Wen-Wen],
Jiang, X.Y.[Xiao-Yan],
Fang, Z.J.[Zhi-Jun],
Gao, Y.B.[Yong-Bin],
TV-Net: A Structure-Level Feature Fusion Network Based on Tensor
Voting for Road Crack Segmentation,
ITS(25), No. 6, June 2024, pp. 5743-5754.
IEEE DOI Code:
WWW Link.
2406
Tensors, Image segmentation, Roads, Feature extraction,
Convolutional neural networks, Eigenvalues and eigenfunctions, U-Net
BibRef
Liang, H.M.[Hai-Mei],
Pagano, R.G.[Rosa Giovanna],
Oddone, S.[Stefano],
Cong, L.[Lin],
de Blasiis, M.R.[Maria Rosaria],
Analysis of Road Surface Texture for Asphalt Pavement Adhesion
Assessment Using 3D Laser Technology,
RS(16), No. 11, 2024, pp. 1943.
DOI Link
2406
BibRef
Zhang, X.B.[Xue-Bing],
Pei, J.X.[Jun-Xuan],
Sha, X.D.[Xian-Da],
Feng, X.[Xuan],
Hu, X.[Xin],
Chen, C.L.[Chang-La],
Song, Z.C.[Zheng-Chun],
Experimental Co-Polarimetric GPR Survey on Artificial Vertical
Concrete Cracks by the Improved Time-Varying Centroid Frequency
Scheme,
RS(16), No. 12, 2024, pp. 2095.
DOI Link
2406
BibRef
Gu, Y.S.[Yang-Song],
Khojastehpour, M.[Mohammad],
Jia, X.Y.[Xiao-Yang],
Han, L.D.[Lee D.],
Estimating Pavement Condition by Leveraging Crowdsourced Data,
RS(16), No. 12, 2024, pp. 2237.
DOI Link
2406
BibRef
Wang, S.Q.[Si-Qi],
Leng, Z.[Zhen],
Sui, X.[Xin],
Zhang, W.G.[Wei-Guang],
Ma, T.[Tao],
Zhu, Z.[Zehui],
Real-Time Asphalt Pavement Layer Thickness Prediction Using
Ground-Penetrating Radar Based on a Modified Extended Common
Mid-Point (XCMP) Approach,
ITS(25), No. 7, July 2024, pp. 6848-6860.
IEEE DOI
2407
Asphalt, Reflection, Dielectric constant, Antennas,
Real-time systems, Mathematical models, Estimation,
extended common mid-point method
BibRef
Ning, Z.P.[Zhi-Peng],
Wang, H.[Hui],
Li, S.L.[Sheng-Lin],
Xu, Z.C.[Zhou-Cong],
YOLOv7-RDD: A Lightweight Efficient Pavement Distress Detection Model,
ITS(25), No. 7, July 2024, pp. 6994-7003.
IEEE DOI
2407
Convolution, Feature extraction, YOLO, Roads,
Maintenance engineering, Kernel, Head, Front-view video data,
urban road
BibRef
Lei, Q.[Qin],
Zhong, J.[Jiang],
Wang, C.[Chen],
Joint Optimization of Crack Segmentation With an Adaptive Dynamic
Threshold Module,
ITS(25), No. 7, July 2024, pp. 6902-6916.
IEEE DOI
2407
Task analysis, Optimization, Instance segmentation,
Semantic segmentation, Optimized production technology, joint optimization
BibRef
Zhang, C.[Cheng],
Shen, S.H.[Shi-Hui],
Huang, H.[Hai],
Yu, S.[Shuai],
In-Situ Dynamic Modulus Prediction for Asphalt Pavement Combining
Machine Learning Algorithm and Sensing Technology,
ITS(25), No. 8, August 2024, pp. 8695-8704.
IEEE DOI
2408
Vehicle dynamics, Artificial neural networks, Predictive models,
Feature extraction, Mechanical sensors, Load modeling,
wireless sensor
BibRef
Yuan, Q.[Qi],
Shi, Y.F.[Yu-Feng],
Li, M.Y.[Ming-Yue],
A Review of Computer Vision-Based Crack Detection Methods in Civil
Infrastructure: Progress and Challenges,
RS(16), No. 16, 2024, pp. 2910.
DOI Link
2408
BibRef
Yu, J.[Jongmin],
Jiang, J.Q.[Jia-Qi],
Fichera, S.[Sebastiano],
Paoletti, P.[Paolo],
Layzell, L.[Lisa],
Mehta, D.[Devansh],
Luo, S.[Shan],
Road Surface Defect Detection: From Image-Based to Non-Image-Based: A
Survey,
ITS(25), No. 9, September 2024, pp. 10581-10603.
IEEE DOI
2409
Roads, Defect detection, Surface cracks, Asphalt, Soil, Surveys, Sensors,
Road surface defect detection, defect detection, crack detection,
deep learning
BibRef
Li, Z.[Zhe],
Torbaghan, M.E.[Mehran Eskandari],
Zhang, T.[Tuo],
Qin, X.[Xia],
Li, W.[Wenda],
Li, Y.J.[Yong-Jian],
Zhang, J.[Jiupeng],
An Automated 3D Crack Severity Assessment Using Surface Data for
Improving Flexible Pavement Maintenance Strategies,
ITS(25), No. 9, September 2024, pp. 12490-12503.
IEEE DOI
2409
Surface cracks, Volume measurement,
Surface morphology, Predictive models, crack volume
BibRef
Sun, L.X.[Li-Xiang],
Yang, Y.X.[Yi-Xin],
Yang, Z.[Zaichun],
Zhou, G.X.[Guo-Xiong],
Li, L.J.[Liu-Jun],
DUCTNet: An Effective Road Crack Segmentation Method in UAV Remote
Sensing Images Under Complex Scenes,
ITS(25), No. 9, September 2024, pp. 12682-12695.
IEEE DOI
2409
Feature extraction, Roads, Image segmentation, Data mining,
Interference, Autonomous aerial vehicles, Training, Complex scenes,
UAV remote sensing image
BibRef
Zhang, H.[Hang],
Zhang, A.A.[Allen A.],
Dong, Z.[Zishuo],
He, A.[Anzheng],
Liu, Y.[Yang],
Zhan, Y.[You],
Wang, K.C.P.[Kelvin C. P.],
Robust Semantic Segmentation for Automatic Crack Detection Within
Pavement Images Using Multi-Mixing of Global Context and Local Image
Features,
ITS(25), No. 9, September 2024, pp. 11282-11303.
IEEE DOI
2409
Transformers, Feature extraction, Convolutional neural networks,
Decoding, Training, Surface cracks, Semantic segmentation,
graph network
BibRef
Li, L.C.[Lin-Chao],
Liu, J.Z.[Jia-Zhen],
Xing, J.[Jiabao],
Liu, Z.Y.[Zhi-Yang],
Lin, K.[Kai],
Du, B.[Bowen],
Road Pothole Detection Based on Crowdsourced Data and Extended Mask
R-CNN,
ITS(25), No. 9, September 2024, pp. 12504-12516.
IEEE DOI
2409
Roads, Computational modeling, Feature extraction, Task analysis,
Inspection, Digital images, Pothole detection,
mask R-CNN
BibRef
Chen, T.Y.[Teng-Yang],
Ren, J.T.[Jiang-Tao],
Integrating GAN and Texture Synthesis for Enhanced Road Damage
Detection,
ITS(25), No. 9, September 2024, pp. 12361-12371.
IEEE DOI
2409
Roads, Task analysis, Generative adversarial networks,
Data augmentation, Training, Data models, Shape, data argumentation
BibRef
Ma, N.[Nachuan],
Fan, R.[Rui],
Xie, L.H.[Li-Hua],
UP-CrackNet: Unsupervised Pixel-Wise Road Crack Detection via
Adversarial Image Restoration,
ITS(25), No. 10, October 2024, pp. 13926-13936.
IEEE DOI
2410
Roads, Image restoration, Training, Anomaly detection, Task analysis,
Semantics, Semantic segmentation, Semantic segmentation,
unsupervised anomaly detection
BibRef
Zhong, J.T.[Jing-Tao],
Ma, Y.[Yuetan],
Zhang, M.M.[Miao-Miao],
Xiao, R.[Rui],
Cheng, G.[Guantao],
Huang, B.S.[Bao-Shan],
A Pavement Crack Translator for Data Augmentation and Pixel-Level
Detection Based on Weakly Supervised Learning,
ITS(25), No. 10, October 2024, pp. 13350-13363.
IEEE DOI
2410
Generative adversarial networks, Image segmentation, Accuracy,
Data augmentation, Image synthesis, Noise, Generators,
pavement crack detection
BibRef
Liu, Z.[Zhen],
Wang, S.Q.[Si-Qi],
Gu, X.Y.[Xing-Yu],
Wang, D.Y.[Dan-Yu],
Dong, Q.[Qiao],
Cui, B.[Bingyan],
Intelligent Assessment of Pavement Structural Conditions: A Novel
FeMViT Classification Network for GPR Images,
ITS(25), No. 10, October 2024, pp. 13511-13523.
IEEE DOI
2410
Roads, Feature extraction, Computational modeling, Transformers,
Asphalt, Image segmentation, YOLO, Intelligent assessment,
feature enhancement
BibRef
Wang, S.X.[Shou-Xing],
Jiao, H.Z.[Hong-Zan],
Su, X.[Xin],
Yuan, Q.Q.[Qiang-Qiang],
An Ensemble Learning Approach With Attention Mechanism for Detecting
Pavement Distress and Disaster-Induced Road Damage,
ITS(25), No. 10, October 2024, pp. 13667-13681.
IEEE DOI Code:
WWW Link.
2410
Roads, Disasters, YOLO, Social networking (online),
Ensemble learning, Training, Detectors, Road damage detection,
attention mechanism
BibRef
Qi, H.C.[Hao-Chen],
Kong, X.W.[Xiang-Wei],
Jin, Z.B.[Zhi-Bo],
Zhang, J.Q.[Ji-Qiang],
Wang, Z.[Zinan],
A Vision-Transformer-Based Convex Variational Network for Bridge
Pavement Defect Segmentation,
ITS(25), No. 10, October 2024, pp. 13820-13832.
IEEE DOI
2410
Bridges, Level set, Decoding, Transformers, Task analysis,
Linear programming, Defect detection, Bridge pavement inspection,
level set function
BibRef
Wang, X.[Xin],
Mao, Z.[Zhaoyong],
Liang, Z.W.[Zhi-Wei],
Shen, J.[Junge],
Multi-Scale Semantic Map Distillation for Lightweight Pavement Crack
Detection,
ITS(25), No. 10, October 2024, pp. 15081-15093.
IEEE DOI
2410
Feature extraction, Semantics, Knowledge engineering, Accuracy,
Convolutional neural networks, Transportation, Training,
pavement crack detection
BibRef
Zhang, Z.Y.[Zhi-Yuan],
Liu, F.[Fang],
Huang, Y.C.[Yu-Cheng],
Hou, Y.[Yue],
Detection and Statistics System of Pavement Distresses Based on
Street View Videos,
ITS(25), No. 10, October 2024, pp. 15106-15115.
IEEE DOI
2410
Roads, Convolution, Feature extraction, Computational modeling,
Videos, Surface cracks, YOLO, Pavement defects, YOLOv8, Slim-neck,
Deep oc-sort
BibRef
Li, P.T.[Peng-Tao],
Wang, M.[Meihua],
Fan, Z.[Zhun],
Huang, H.[Han],
Zhu, G.[Guijie],
Zhuang, J.[Jiafan],
OUR-Net: A Multi-Frequency Network With Octave Max Unpooling and
Octave Convolution Residual Block for Pavement Crack Segmentation,
ITS(25), No. 10, October 2024, pp. 13833-13848.
IEEE DOI
2410
Feature extraction, Image segmentation, Convolution,
Image edge detection, Decoding, Surface cracks, Redundancy,
multi-spatial frequency features
BibRef
Liu, C.Q.[Chuan-Qi],
Zhao, J.K.[Jian-Kang],
Zhu, C.G.[Cheng-Guang],
Xia, X.[Xuan],
Long, H.H.[Hai-Hui],
MECFNet: Reconstruct Sharp Image for UAV-Based Crack Detection,
ITS(25), No. 10, October 2024, pp. 15016-15028.
IEEE DOI
2410
Cameras, Image restoration, Task analysis, Transformers, Kernel,
Image reconstruction, Feature extraction, Crack detection,
cross-modal transformer
BibRef
Li, J.[Jie],
Qu, Z.[Zhong],
Wang, S.Y.[Shi-Yan],
Xia, S.F.[Shu-Fang],
YOLOX-RDD: A Method of Anchor-Free Road Damage Detection for
Front-View Images,
ITS(25), No. 10, October 2024, pp. 14725-14739.
IEEE DOI
2410
Roads, Feature extraction, Convolution, Detectors, Deep learning, Neck,
Adaptation models, Road damage detection, anchor-free,
deep learning
BibRef
Cheng, H.Y.[Hao-Yuan],
Zhang, B.[Bei],
Zhong, Y.H.[Yan-Hui],
Xu, S.J.[Sheng-Jie],
Quantitative Pixel-Level Segmentation and 3D Reconstruction of
Concealed Cracks in Asphalt Pavements,
ITS(25), No. 11, November 2024, pp. 18136-18152.
IEEE DOI
2411
Ground penetrating radar, Asphalt, Accuracy, Image segmentation,
Finite difference methods, Time-domain analysis,
3D reconstruction
BibRef
Zhang, Y.[Yu],
Zhang, L.[Lin],
Detection of Pavement Cracks by Deep Learning Models of Transformer
and UNet,
ITS(25), No. 11, November 2024, pp. 15791-15808.
IEEE DOI
2411
Transformers, Image segmentation, Task analysis, Computational modeling,
Convolutional neural networks, Accuracy, CNN
BibRef
Shan, J.H.[Jin-Huan],
Jiang, W.[Wei],
Huang, Y.[Yue],
Yuan, D.D.[Dong-Dong],
Liu, Y.[Yaohan],
Unmanned Aerial Vehicle (UAV)-Based Pavement Image Stitching Without
Occlusion, Crack Semantic Segmentation, and Quantification,
ITS(25), No. 11, November 2024, pp. 17038-17053.
IEEE DOI
2411
Accuracy, Semantic segmentation, Autonomous aerial vehicles, Roads,
Inspection, Task analysis, Image stitching, Pavement distress,
unmanned aerial vehicle (UAV)
BibRef
Zhang, Y.C.[Ying-Chao],
Liu, C.[Cheng],
Real-Time Pavement Damage Detection With Damage Shape Adaptation,
ITS(25), No. 11, November 2024, pp. 18954-18963.
IEEE DOI
2411
Accuracy, YOLO, Transformers, Sensors, Roads, Detection algorithms,
Non-destructive testing, transformer, damage detection, real-time detection
BibRef
Pham, S.V.H.[Son Vu Hong],
Nguyen, K.V.T.[Khoi Van Tien],
Le, L.H.[Long Hoai],
Dang, N.T.N.[Nghiep Trinh Nguyen],
Developing RTI IMS Software to Autonomously Manage Road Surface
Quality, Adapting to Environmental Impacts,
ITS(25), No. 11, November 2024, pp. 18472-18484.
IEEE DOI
2411
Climate change, Intelligent systems, Construction industry,
Management, Environmental factors, Surface cracks, Road safety,
construction management
BibRef
Li, X.R.[Xin-Ran],
Xu, X.Y.[Xiang-Yang],
Yang, H.[Hao],
A Road Crack Detection Model Integrating GLMANet and EFPN,
ITS(25), No. 11, November 2024, pp. 18211-18223.
IEEE DOI
2411
Feature extraction, Roads, Convolution, Image edge detection,
Semantics, Convolutional neural networks, Data mining,
feature pyramid network
BibRef
Ma, M.Y.[Ming-Yang],
Yang, L.[Lei],
Liu, Y.H.[Yan-Hong],
Yu, H.N.[Hong-Nian],
A Transformer-Based Network With Feature Complementary Fusion for
Crack Defect Detection,
ITS(25), No. 11, November 2024, pp. 16989-17006.
IEEE DOI
2411
Feature extraction, Transformers, Task analysis, Image coding, Encoding,
Computational modeling, Convolutional neural networks, crack detection
BibRef
Chen, Z.Z.[Zhuang-Zhuang],
Lu, R.H.[Rong-Hao],
Chen, J.[Jie],
Song, H.B.H.[Hou-Bing Herbert],
Li, J.Q.[Jian-Qiang],
Implicit Gradient-Modulated Semantic Data Augmentation for Deep Crack
Recognition,
ITS(25), No. 11, November 2024, pp. 16084-16095.
IEEE DOI
2411
Semantics, Training, Data augmentation, Task analysis, Deep learning,
Upper bound, Feature extraction, semantic data augmentation
BibRef
Zhu, J.Q.[Jun-Qing],
Wu, Y.X.[Yu-Xuan],
Ma, T.[Tao],
Multi-Object Detection for Daily Road Maintenance Inspection With UAV
Based on Improved YOLOv8,
ITS(25), No. 11, November 2024, pp. 16548-16560.
IEEE DOI
2411
Roads, Maintenance, Inspection, Autonomous aerial vehicles,
Feature extraction, Task analysis, Accuracy, deep learning
BibRef
Liu, Z.[Zihan],
Jing, K.F.[Kai-Feng],
Yang, K.[Kai],
Zhang, Z.J.[Zhi-Jun],
Li, X.J.[Xi-Jie],
Efficient dense attention fusion network with channel correlation
loss for road damage detection,
IET-ITS(18), No. 10, 2024, pp. 1747-1759.
DOI Link
2411
data analysis, image processing, road safety
BibRef
Zhao, T.[Tong],
Yang, L.[Lei],
Xie, Y.C.[Yi-Chen],
Ding, M.Y.[Ming-Yu],
Tomizuka, M.[Masayoshi],
Wei, Y.[Yintao],
RoadBEV: Road Surface Reconstruction in Bird's Eye View,
ITS(25), No. 11, November 2024, pp. 19088-19099.
IEEE DOI Code:
WWW Link.
2411
Roads, Image reconstruction, Surface reconstruction, Estimation, Geometry,
Cameras, Accuracy, Bird's eye view, 3D reconstruction, autonomous driving
BibRef
Shan, W.[Wei],
Xu, G.C.[Guang-Chao],
Hou, P.[Peijie],
Du, H.[Helong],
Du, Y.T.[Ya-Ting],
Guo, Y.[Ying],
Spatiotemporal Evolution Analysis of Surface Deformation on the
Beihei Highway Based on Multi-Source Remote Sensing Data,
RS(16), No. 21, 2024, pp. 4091.
DOI Link
2411
BibRef
Bu, T.X.[Tian-Xiang],
Zhu, J.Q.[Jun-Qing],
Ma, T.[Tao],
Jiang, S.[Shun],
Pavement Point Cloud Upsampling Based on Transformer: Toward
Enhancing 3D Pavement Data,
ITS(25), No. 12, December 2024, pp. 21647-21657.
IEEE DOI
2412
Point cloud compression, Accuracy, Roads, Feature extraction,
Transformers, Costs, Point cloud upsampling, deep learning
BibRef
Chen, C.J.[Chun-Jiang],
Song, Y.Z.[Yong-Ze],
Shemery, A.[Ammar],
Hampson, K.[Keith],
Dewan, A.[Ashraf],
Zhong, Y.[Yun],
Wu, P.[Peng],
Large Scale Pavement Crack Evaluation Through a Novel Spatial Machine
Learning Approach Considering Geocomplexity,
ITS(25), No. 12, December 2024, pp. 21429-21441.
IEEE DOI
2412
Roads, Inspection, Numerical models, Maintenance, Data models,
Australia, Visualization, Accuracy, Load modeling, Analytical models,
laser scanning
BibRef
Zhang, Y.M.[Yi-Ming],
Tong, Z.[Zheng],
She, X.[Xuhui],
Wang, S.Q.[Si-Qi],
Zhang, W.G.[Wei-Guang],
Fan, J.W.[Jian-Wei],
Cheng, H.[Hanglin],
Yang, H.[Handuo],
Cao, J.[Jinde],
SWC-Net and Multi-Phase Heterogeneous FDTD Model for Void Detection
Underneath Airport Pavement Slab,
ITS(25), No. 12, December 2024, pp. 20698-20714.
IEEE DOI
2412
Slabs, Airports, Time-domain analysis, Finite difference methods,
Aggregates, Atmospheric modeling, Morphology, Solid modeling,
void underneath slab
BibRef
Tao, H.J.[Huan-Jie],
Weakly-Supervised Pavement Surface Crack Segmentation Based on Dual
Separation and Domain Generalization,
ITS(25), No. 12, December 2024, pp. 19729-19743.
IEEE DOI
2412
Image segmentation, Annotations, Training, Surface cracks,
Power capacitors, Manuals, Image reconstruction, Data models,
image-level labels
BibRef
Zhou, W.[Wei],
Huang, H.[Hongpu],
Zhang, H.C.[Han-Cheng],
Wang, C.[Chen],
Teaching Segment-Anything-Model Domain-Specific Knowledge for Road
Crack Segmentation From On-Board Cameras,
ITS(25), No. 12, December 2024, pp. 20588-20601.
IEEE DOI Code:
WWW Link.
2412
Roads, Image segmentation, Cameras, Training, Adaptation models,
Computational modeling, Transfer learning, Inspection, on-board cameras
BibRef
Zhao, S.G.[Shu-Guang],
Yi, W.[Wen],
Shi, J.J.[Jia-Ji],
Jiang, Z.[Zhengru],
Lu, X.C.[Xiao-Chen],
An Innovative Crack Detection Algorithm Based on Efficient Feature
Fusion and Progressive Transfer Learning,
ITS(25), No. 12, December 2024, pp. 21469-21483.
IEEE DOI
2412
Feature extraction, Accuracy, Bridges, Transfer learning, Data models,
Training, Computational modeling, Transformers, transfer learning (TL)
BibRef
Li, H.T.[Hai-Tao],
Peng, T.[Tao],
Qiao, N.G.[Ning-Guo],
Guan, Z.W.[Zhi-Wei],
Feng, X.Y.[Xin-Yun],
Guo, P.[Peng],
Duan, T.T.[Ting-Ting],
Gong, J.F.[Jin-Feng],
CrackTinyNet: A novel deep learning model specifically designed for
superior performance in tiny road surface crack detection,
IET-ITS(18), No. 12, 2024, pp. 2693-2712.
DOI Link
2501
crack detection, object detection, road safety, road traffic
BibRef
Zhang, R.H.[Rong-Hui],
Yang, S.Y.[Shang-Yu],
Lyu, D.[Dakang],
Wang, Z.[Zihan],
Chen, J.Z.[Jun-Zhou],
Ren, Y.L.[Yi-Long],
Gao, B.L.[Bo-Lin],
Lv, Z.H.[Zhi-Han],
AGSENet: A Robust Road Ponding Detection Method for Proactive Traffic
Safety,
ITS(26), No. 1, January 2025, pp. 497-516.
IEEE DOI Code:
WWW Link.
2501
Roads, Feature extraction, Reflection, Support vector machines,
Convolutional neural networks, Accuracy, Accidents,
proactive traffic safety
BibRef
Tao, R.[Rui],
Peng, R.[Rui],
Jin, Y.[Yong],
Gong, F.Y.[Fang-Yuan],
Li, B.[Bo],
Automatic Detection of Asphalt Pavement Crack Width Based on Machine
Vision,
ITS(26), No. 1, January 2025, pp. 484-496.
IEEE DOI
2501
Roads, Asphalt, Maintenance, Surface cracks, Noise, Diseases, Training,
Convolutional neural networks, Complexity theory,
road maintenance
BibRef
Wang, Z.[Zhengfang],
Zhu, H.L.[Hong-Liang],
Yang, Y.J.[Yu-Jie],
Jiang, H.[Haonan],
Li, W.H.[Wen-Hao],
Li, B.[Bingrui],
Li, P.[Peng],
Xu, L.[Lei],
Sui, Q.[Qingmei],
Wang, J.[Jing],
A Pavement Crack Registration and Change Identification Method Based
on Unsupervised Deep Neural Network,
ITS(26), No. 1, January 2025, pp. 757-769.
IEEE DOI
2501
Feature extraction, Autonomous aerial vehicles,
Image registration, Inspection, Convolutional neural networks,
multi-temporal UAV images
BibRef
Cui, B.[Bingyan],
Wang, H.[Hao],
Predicting Asphalt Pavement Deterioration Under Climate Change
Uncertainty Using Bayesian Neural Network,
ITS(26), No. 1, January 2025, pp. 785-797.
IEEE DOI
2501
Meteorology, Predictive models, Data models, Uncertainty,
Climate change, Rough surfaces, Asphalt, Adaptation models,
uncertainty analysis
BibRef
Qu, Z.[Zhong],
Wang, J.D.[Jian-Dong],
Yin, X.H.[Xue-Hui],
A Directional Connectivity Feature Enhancement Network for Pavement
Crack Detection,
ITS(26), No. 1, January 2025, pp. 1039-1054.
IEEE DOI
2501
Feature extraction, Convolution, Semantics, Accuracy, Noise, Topology,
Background noise, Strips, Shape, Digital images, Crack detection,
directional connectivity
BibRef
Wu, W.H.[Wen-Hua],
Wang, Q.[Qi],
Wang, G.M.[Guang-Ming],
Wang, J.P.[Jun-Ping],
Zhao, T.[Tiankun],
Liu, Y.[Yang],
Gao, D.[Dongchao],
Liu, Z.[Zhe],
Wang, H.S.[He-Sheng],
EMIE-MAP: Large-scale Road Surface Reconstruction Based on Explicit
Mesh and Implicit Encoding,
ECCV24(LXXXVII: 370-386).
Springer DOI
2412
BibRef
Jaziri, A.[Achref],
Mundt, M.[Martin],
Rodriguez, A.F.[Andres Fernandez],
Ramesh, V.[Visvanathan],
Designing a Hybrid Neural System to Learn Real-world Crack
Segmentation from Fractal-based Simulation,
WACV24(8621-8631)
IEEE DOI
2404
Symbiosis, Adaptation models, Fractals, Data models, Surface cracks,
Task analysis, Applications,
Image recognition and understanding
BibRef
Kumari, S.[Shruti],
Gautam, A.[Anjali],
Basak, S.[Suvramalya],
Saxena, N.[Nidhi],
YOLOv8 Based Deep Learning Method for Potholes Detection,
ICCVMI23(1-6)
IEEE DOI
2403
Training, YOLO, Adaptation models, Shape, Roads, Supervised learning,
Maintenance engineering, Pothole detection, Deep learning,
YOLOv8
BibRef
Wu, W.X.[Wen-Xiu],
Zhou, X.Y.[Xiao-Yong],
Jin, Y.H.[Yi-Hui],
Fang, Z.H.[Zhi-Hua],
Fan, X.Q.[Xia-Qi],
Zhang, B.[Biao],
Zheng, R.J.[Rui-Jian],
A Method to Detect Pavement Surface Distress Based on Improved U-Net
Semantic Segmentation Network,
CVIDL23(625-630)
IEEE DOI
2403
Training, Deep learning, Semantic segmentation, Roads,
Maintenance engineering, Feature extraction, Safety, data augmentation
BibRef
Tian, B.H.[Bao-Hui],
Liu, A.X.[Ao-Xiang],
Yang, H.[He],
Liu, Y.[Yong],
Wang, J.[Juan],
Xu, G.C.[Gao-Cheng],
Zheng, H.[Hui],
Cai, H.[HongYue],
Zhang, T.X.[Tian-Xiao],
Pavement contour extraction and material recognition based on
landscape camera,
CVIDL23(318-322)
IEEE DOI
2403
Deep learning, Image recognition, Roads, Semantic segmentation,
Digital transformation, Maintenance engineering, road maintenance
BibRef
Liu, Q.[Qian],
Zhu, C.[Chuanhui],
Automatic Detection for Road Voids from GPR Images using Deep
Learning Method,
CVIDL23(617-620)
IEEE DOI
2403
Deep learning, Image recognition, Ground penetrating radar,
Target recognition, Roads, Computational modeling,
Road Detection
BibRef
Vojír, T.[Tomá],
Matas, J.G.[Jirí G.],
Image-Consistent Detection of Road Anomalies as Unpredictable Patches,
WACV23(5480-5489)
IEEE DOI
2302
Filtering, Roads, Design methodology, Benchmark testing,
Feature extraction, Task analysis, segmentation.
BibRef
Zavrtanik, V.[Vitjan],
Kristan, M.[Matej],
Skocaj, D.[Danijel],
DSR: A Dual Subspace Re-Projection Network for Surface Anomaly
Detection,
ECCV22(XXXI:539-554).
Springer DOI
2211
BibRef
Cordes, K.[Kai],
Reinders, C.[Christoph],
Hindricks, P.[Paul],
Lammers, J.[Jonas],
Rosenhahn, B.[Bodo],
Broszio, H.[Hellward],
RoadSaW: A Large-Scale Dataset for Camera-Based Road Surface and
Wetness Estimation,
WAD22(4439-4448)
IEEE DOI
2210
Uncertainty, Target tracking, Roads, Friction, Current measurement,
Estimation, Streaming media
BibRef
Lank, M.[Martin],
Friedjungová, M.[Magda],
Road Quality Classification,
CIAP22(II:553-563).
Springer DOI
2205
BibRef
Vojir, T.[Tomas],
ipka, T.[Tomá],
Aljundi, R.[Rahaf],
Chumerin, N.[Nikolay],
Reino, D.O.[Daniel Olmeda],
Matas, J.G.[Jiri G.],
Road Anomaly Detection by Partial Image Reconstruction with
Segmentation Coupling,
ICCV21(15631-15640)
IEEE DOI
2203
Couplings, Training, Surface reconstruction, Roads, Semantics,
Transform coding, Tires,
Scene analysis and understanding
BibRef
Nayyeri, F.[Fereshteh],
Zhou, J.[Jun],
Multi-Resolution ResNet for Road and Bridge Crack Detection,
DICTA21(1-8)
IEEE DOI
2201
Training, Bridges, Image resolution, Computational modeling, Roads,
Image edge detection, Digital images, crack detection, ResNet,
crack dataset
BibRef
Shahbazi, L.[Leila],
Majidi, B.[Babak],
Movaghar, A.[Ali],
Autonomous Road Pavement Inspection and Defect Analysis for Smart
City Maintenance,
IPRIA21(1-5)
IEEE DOI
2201
Deep learning, Visualization, Asphalt, Smart cities, Roads, Inspection,
Safety, Road pavement crack detection,
smart city
BibRef
Duan, L.J.[Li-Juan],
Zeng, J.[Jun],
Pang, J.B.[Jun-Biao],
Wang, J.Z.[Jun-Zhe],
Pavement Crack Detection Using Multi-stage Structural Feature
Extraction Model,
ICIP21(969-973)
IEEE DOI
2201
Training, Art, Roads, Maintenance engineering, Feature extraction,
Complexity theory, crack detection, deep supervision,
structural feature extraction
BibRef
Zhang, Y.J.[Yu-Jia],
Li, Q.Z.[Qian-Zhong],
Zhao, X.G.[Xiao-Guang],
Tan, M.[Min],
TB-Net: A Three-Stream Boundary-Aware Network for Fine-Grained
Pavement Disease Segmentation,
WACV21(3654-3663)
IEEE DOI
2106
Convolution, Roads, Inspection, Maintenance engineering, Safety
BibRef
Masihullah, S.[Shaik],
Garg, R.[Ritu],
Mukherjee, P.[Prerana],
Ray, A.[Anupama],
Attention Based Coupled Framework for Road and Pothole Segmentation,
ICPR21(5812-5819)
IEEE DOI
2105
Training, Image segmentation, Visualization, Rain, Roads, Snow,
Vehicle safety, Pothole Detection, Road Segmentation,
Deep Networks
BibRef
Wu, X.Y.[Xuan-Yi],
Ma, J.F.[Jian-Fei],
Sun, Y.[Yu],
Zhao, C.[Chenqiu],
Basu, A.[Anup],
Multi-Scale Deep Pixel Distribution Learning for Concrete Crack
Detection,
ICPR21(6577-6583)
IEEE DOI
2105
Deep learning, Learning systems, Image segmentation,
Feature extraction, Surface cracks,
concrete crack detection
BibRef
Inoue, Y.[Yuki],
Nagayoshi, H.[Hiroto],
Crack Detection as a Weakly-Supervised Problem: Towards Achieving
Less Annotation-Intensive Crack Detectors,
ICPR21(65-72)
IEEE DOI
2105
Annotations, Roads, Semantics, Buildings, Brightness, Detectors, Inspection
BibRef
Chitale, P.A.,
Kekre, K.Y.,
Shenai, H.R.,
Karani, R.,
Gala, J.P.,
Pothole Detection and Dimension Estimation System using Deep Learning
(YOLO) and Image Processing,
IVCNZ20(1-6)
IEEE DOI
2012
Deep learning, Pandemics, Shape, Roads, Image processing, Estimation,
Maintenance engineering, YOLO, Deep Learning,
Dimension Estimation
BibRef
Cannelle, B.,
Beltzung, F.,
Thiémard-Spada, M.,
Application of Photogrammetry and Image Processing for the Study Of
Porous Surface Courses,
ISPRS20(B2:745-749).
DOI Link
2012
BibRef
Ravi, R.,
Bullock, D.,
Habib, A.,
Highway and Airport Runway Pavement Inspection Using Mobile Lidar,
ISPRS20(B1:349-354).
DOI Link
2012
BibRef
Pontoglio, E.,
Colucci, E.,
Lingua, A.,
Maschio, P.,
Migliazza, M.R.,
Scavia, C.,
UAV and Close-range Photogrammetry to Support Geo-mechanical Analysis
In Safety Road Management: the 'Vallone d'Elva' Road,
ISPRS20(B2:1159-1166).
DOI Link
2012
BibRef
Pinto, L.,
Bianchini, F.,
Nova, V.,
Passoni, D.,
Low-cost UAS Photogrammetry for Road Infrastructures' Inspection,
ISPRS20(B2:1145-1150).
DOI Link
2012
BibRef
Ono, Y.,
Tsuji, A.,
Abe, J.,
Noguchi, H.,
Abe, J.,
Robust Detection of Surface Anomaly Using Lidar Point Cloud With
Intensity,
ISPRS20(B2:1129-1136).
DOI Link
2012
BibRef
Shokri, P.,
Shahbazi, M.,
Lichti, D.,
Nielsen, J.,
Vision-based Approaches for Quantifying Cracks In Concrete Structures,
ISPRS20(B2:1167-1174).
DOI Link
2012
BibRef
Niu, B.,
Wu, H.,
Meng, Y.,
Application of CEM Algorithm in the Field of Tunnel Crack
Identification,
ICIVC20(232-236)
IEEE DOI
2009
Feature extraction, Gabor filters, Road transportation,
Filtering algorithms, Image edge detection, Inspection,
CEM
BibRef
Benz, C.,
Debus, P.,
Ha, H.K.,
Rodehorst, V.,
Crack Segmentation on UAS-based Imagery using Transfer Learning,
IVCNZ19(1-6)
IEEE DOI
2004
Code, Crack Detection.
WWW Link. autonomous aerial vehicles, convolutional neural nets,
crack detection, image resolution, image segmentation,
UAS
BibRef
Park, J.S.,
Lee, K.S.,
Kim, S.,
Assessment for a Condition Using Terrestrial Lidar Data,
Gi4DM19(311-314).
DOI Link
1912
Potholes, etc.
BibRef
d'Aranno, P.,
di Benedetto, A.,
Fiani, M.,
Marsella, M.,
Remote Sensing Technologies for Linear Infrastructure Monitoring,
GEORES19(461-468).
DOI Link
1912
E.g. roads.
BibRef
Liebold, F.,
Maas, H.G.,
Heravi, A.A.,
Crack Width Measurement for Non-planar Surfaces By Triangle Mesh
Analysis in Civil Engineering Material Testing,
Optical3D19(107-113).
DOI Link
1912
BibRef
Seydi, S.T.,
Rastiveis, H.,
A Deep Learning Framework for Roads Network Damage Assessment Using
Post-earthquake Lidar Data,
SMPR19(955-961).
DOI Link
1912
BibRef
Fakhri, S.A.,
Fakhri, S.A.,
Saadatseresht, M.,
Road Crack Detection Using Gaussian/prewitt Filter,
SMPR19(371-377).
DOI Link
1912
BibRef
Truong-Hong, L.,
Laefer, D.F.,
Lindenbergh, R.C.,
Automatic Detection of Road Edges From Aerial Laser Scanning Data,
Laser19(1135-1140).
DOI Link
1912
BibRef
van der Horst, B.B.,
Lindenbergh, R.C.,
Puister, S.W.J.,
Mobile Laser Scan Data for Road Surface Damage Detection,
Laser19(1141-1148).
DOI Link
1912
BibRef
König, J.,
Jenkins, M.D.[M. David],
Barrie, P.,
Mannion, M.,
Morison, G.,
A Convolutional Neural Network for Pavement Surface Crack
Segmentation Using Residual Connections and Attention Gating,
ICIP19(1460-1464)
IEEE DOI
1910
Semantic Segmentation, Attention, Residual Connections, U-Net, Surface Cracks
BibRef
Dhiman, A.,
Chien, H.,
Klette, R.,
Road surface distress detection in disparity space,
IVCNZ17(1-6)
IEEE DOI
1902
road accidents, road traffic, roads, stereo image processing,
road surface distress detection, traffic accidents,
Sensors
BibRef
Yang, L.,
Li, B.,
Li, W.,
Jiang, B.,
Xiao, J.,
Semantic Metric 3D Reconstruction for Concrete Inspection,
Odometry18(1624-16248)
IEEE DOI
1812
Inspection, Semantics, Measurement,
Visualization, Simultaneous localization and mapping, Image segmentation
BibRef
Song, W.,
Workman, S.,
Hadzic, A.,
Zhang, X.,
Green, E.,
Chen, M.,
Souleyrette, R.,
Jacobs, N.,
FARSA: Fully Automated Roadway Safety Assessment,
WACV18(521-529)
IEEE DOI
1806
image processing, neural nets, road safety, roads,
traffic engineering computing, FARSA, US Road Assessment Program,
Training
BibRef
Liu, X.Z.[Xiang-Zeng],
Ai, Y.F.[Yun-Feng],
Scherer, S.[Sebastian],
Robust image-based crack detection in concrete structure using
multi-scale enhancement and visual features,
ICIP17(2304-2308)
IEEE DOI
1803
Indexes, Crack detection, concrete structure, guided filter, image enhancement
BibRef
Güldür Erkal, B.,
Apaydin, N.M.,
Bridge Surface Damage Detection Application with A Laser-based Software
Prototype,
GeoAdvances17(55-57).
DOI Link
1805
BibRef
Grünauer, A.[Andreas],
Halmetschlager-Funek, G.[Georg],
Prankl, J.[Johann],
Vincze, M.[Markus],
Learning the Floor Type for Automated Detection of Dirt Spots for
Robotic Floor Cleaning Using Gaussian Mixture Models,
CVS17(576-589).
Springer DOI
1711
BibRef
Chaudhury, S.,
Nakano, G.,
Takada, J.,
Iketani, A.,
Spatial-Temporal Motion Field Analysis for Pixelwise Crack Detection
on Concrete Surfaces,
WACV17(336-344)
IEEE DOI
1609
Bridges, Concrete, Labeling, Loading, Maintenance engineering, Safety,
Surface cracks.
BibRef
Martínez-Sánchez, J.,
Puente, I.,
GonzálezJorge, H.,
Riveiro, B.,
Arias, P.,
Automatic Thickness And Volume Estimation Of Sprayed Concrete On
Anchored Retaining Walls From Terrestrial Lidar Data,
ISPRS16(B5: 521-526).
DOI Link
1610
BibRef
Abdic, I.,
Fridman, L.,
Brown, D.E.,
Angell, W.,
Reimer, B.,
Marchi, E.,
Schuller, B.,
Detecting road surface wetness from audio: A deep learning approach,
ICPR16(3458-3463)
IEEE DOI
1705
Cameras, Data collection, Recurrent neural networks, Roads,
Rough surfaces, Spectrogram, Tires
BibRef
Vandoni, J.,
Le Hégarat-Mascle, S.,
Aldea, E.,
Crack detection based on a Marked Point Process model,
ICPR16(3933-3938)
IEEE DOI
1705
Adaptation models, Data models, Extremities, Image segmentation,
Joining processes, Roads, Robustness
BibRef
Kil, D.H., and
Shin, F.B.,
Automatic Road-Distress Classification and Identification Using a
Combination of Hierarchical Classifiers and Expert Systems-Object
Processing,
ICIP97(II: 414-417).
IEEE DOI
9710
BibRef
Chapter on Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection continues in
Inspection -- Paint and Printing Quality, Print Analysis .