Li, Q.Q.[Qing-Quan],
Chen, Z.P.[Zhi-Peng],
Hu, Q.W.[Qing-Wu],
A Model-Driven Approach for 3D Modeling of Pylon from Airborne LiDAR
Data,
RS(7), No. 9, 2015, pp. 11501.
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BibRef
Conde, B.[Borja],
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Cabaleiro, M.[Manuel],
Gonzalez-Aguilera, D.[Diego],
Geometrical Issues on the Structural Analysis of Transmission
Electricity Towers Thanks to Laser Scanning Technology and Finite
Element Method,
RS(7), No. 9, 2015, pp. 11551.
DOI Link
1511
BibRef
Guo, B.[Bo],
Huang, X.F.[Xian-Feng],
Li, Q.Q.[Qing-Quan],
Zhang, F.[Fan],
Zhu, J.S.[Jia-Song],
Wang, C.S.[Chi-Sheng],
A Stochastic Geometry Method for Pylon Reconstruction from Airborne
LiDAR Data,
RS(8), No. 3, 2016, pp. 243.
DOI Link
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BibRef
Zhou, R.[Ruqin],
Jiang, W.[Wanshou],
Huang, W.[Wei],
Xu, B.[Bo],
Jiang, S.[San],
A Heuristic Method for Power Pylon Reconstruction from Airborne LiDAR
Data,
RS(9), No. 11, 2017, pp. xx-yy.
DOI Link
1712
BibRef
Cerón, A.[Alexander],
Mondragón, I.[Iván],
Prieto, F.[Flavio],
Real-time transmission tower detection from video based on a feature
descriptor,
IET-CV(11), No. 1, February 2017, pp. 33-42.
DOI Link
1703
BibRef
Shi, Z.W.[Zhen-Wei],
Kang, Z.Z.[Zhi-Zhong],
Lin, Y.[Yi],
Liu, Y.[Yu],
Chen, W.[Wei],
Automatic Recognition of Pole-Like Objects from Mobile Laser Scanning
Point Clouds,
RS(10), No. 12, 2018, pp. xx-yy.
DOI Link
1901
BibRef
Liu, L.[Lianguang],
Du, R.[Rujun],
Liu, W.[Wenlin],
Flood Distance Algorithms and Fault Hidden Danger Recognition for
Transmission Line Towers Based on SAR Images,
RS(11), No. 14, 2019, pp. xx-yy.
DOI Link
1908
BibRef
Chen, S.C.[Shi-Chao],
Wang, C.[Cheng],
Dai, H.Y.[Hua-Yang],
Zhang, H.B.[He-Bing],
Pan, F.F.[Fei-Fei],
Xi, X.H.[Xiao-Huan],
Yan, Y.G.[Yue-Guan],
Wang, P.[Pu],
Yang, X.B.[Xue-Bo],
Zhu, X.X.[Xiao-Xiao],
Aben, A.[Ardana],
Power Pylon Reconstruction Based on Abstract Template Structures
Using Airborne LiDAR Data,
RS(11), No. 13, 2019, pp. xx-yy.
DOI Link
1907
BibRef
Awrangjeb, M.[Mohammad],
Extraction of Power Line Pylons and Wires Using Airborne LiDAR Data
at Different Height Levels,
RS(11), No. 15, 2019, pp. xx-yy.
DOI Link
1908
BibRef
Munir, N.[Nosheen],
Awrangjeb, M.[Mohammad],
Stantic, B.[Bela],
Extraction of Forest Power Lines from LiDAR Point Cloud Data,
DICTA21(01-06)
IEEE DOI
2201
Image segmentation, Solid modeling, Shape, Poles and towers,
Vegetation mapping, Forestry, power lines, pylons, vegetation, span, bundles
See also Effective Selection of Variable Point Neighbourhood for Feature Point Extraction from Aerial Building Point Cloud Data.
BibRef
Awrangjeb, M.,
Jonas, D.,
Zhou, J.,
An Automatic Technique for Power Line Pylon Detection from Point
Cloud Data,
DICTA17(1-8)
IEEE DOI
1804
feature extraction, object detection, trees (mathematics),
candidate pylons, connected component analysis,
Wires
BibRef
Knyaz, V.A.[Vladimir A.],
Kniaz, V.V.[Vladimir V.],
Remondino, F.[Fabio],
Zheltov, S.Y.[Sergey Y.],
Gruen, A.[Armin],
3D Reconstruction of a Complex Grid Structure Combining UAS Images
and Deep Learning,
RS(12), No. 19, 2020, pp. xx-yy.
DOI Link
2010
radio or television towers.
BibRef
Kniaz, V.V.[Vladimir V.],
Zheltov, S.Y.[Sergey Y.],
Remondino, F.[Fabio],
Knyaz, V.A.[Vladimir A.],
Bordodymov, A.,
Gruen, A.[Armin],
Wire Structure Image-based 3d Reconstruction Aided By Deep Learning,
ISPRS20(B2:435-441).
DOI Link
2012
BibRef
Qiao, S.J.[Si-Jia],
Sun, Y.[Yu],
Zhang, H.P.[Hao-Peng],
Deep Learning Based Electric Pylon Detection in Remote Sensing Images,
RS(12), No. 11, 2020, pp. xx-yy.
DOI Link
2006
BibRef
McCulloch, J.[Josh],
Green, R.[Richard],
Conductor Reconstruction for Dynamic Line Rating Using
Vehicle-Mounted LiDAR,
RS(12), No. 22, 2020, pp. xx-yy.
DOI Link
2011
BibRef
Earlier:
Utility pole extraction using vehicle-mounted LIDAR for dynamic line
rating,
IVCNZ17(1-5)
IEEE DOI
1902
BibRef
And:
Density Based Recovery of Urban Power Lines Using Vehicle-Mounted
LiDAR,
IVCNZ18(1-5)
IEEE DOI
1902
BibRef
Earlier:
Extraction of utility poles in LIDAR scans using cross-sectional
slices,
ICVNZ16(1-4)
IEEE DOI
1701
Conductors, Meters, Laser radar, Clustering algorithms,
Poles and towers, Urban areas, lidar.
optical radar, principal component analysis, radar clutter,
road vehicle radar, utility pole extraction,
dynamic line rating.
Clustering algorithms
BibRef
Tarighat, F.[Fereshteh],
Foroughnia, F.[Fatemeh],
Perissin, D.[Daniele],
Monitoring of Power Towers' Movement Using Persistent Scatterer SAR
Interferometry in South West of Tehran,
RS(13), No. 3, 2021, pp. xx-yy.
DOI Link
2102
BibRef
Arastounia, M.[Mostafa],
Lichti, D.D.[Derek D.],
Simultaneous identification, modeling and registration refinement of
poles using laser scanning point clouds,
PandRS(181), 2021, pp. 327-344.
Elsevier DOI
2110
Point cloud, Pole extraction, As-built modeling, Mapping, And laser scanning
BibRef
Lu, Z.[Zhumao],
Gong, H.[Hao],
Jin, Q.[Qiuheng],
Hu, Q.W.[Qing-Wu],
Wang, S.H.[Shao-Hua],
A Transmission Tower Tilt State Assessment Approach Based on Dense
Point Cloud from UAV-Based LiDAR,
RS(14), No. 2, 2022, pp. xx-yy.
DOI Link
2201
BibRef
Li, J.N.[Jia-Nan],
Li, Y.[Yu],
Jiang, H.N.[Hao-Nan],
Zhao, Q.H.[Quan-Hua],
Hierarchical Transmission Tower Detection from High-Resolution SAR
Image,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link
2202
BibRef
Wang, J.[Jingru],
Wang, C.[Cheng],
Xi, X.H.[Xiao-Huan],
Wang, P.[Pu],
Du, M.[Meng],
Nie, S.[Sheng],
Location and Extraction of Telegraph Poles from Image Matching-Based
Point Clouds,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link
2202
BibRef
Huang, Z.Y.[Zhao-Yang],
Wang, F.[Feng],
You, H.J.[Hong-Jian],
Hu, Y.X.[Yu-Xin],
Imaging Parameters-Considered Slender Target Detection in Optical
Satellite Images,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link
2204
BibRef
Liu, C.[Chun],
Yang, J.[Jian],
Ou, J.H.[Jiang-Hong],
Fan, D.[Dahua],
Offshore Oil Platform Detection in Polarimetric SAR Images Using
Level Set Segmentation of Limited Initial Region and Convolutional
Neural Network,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link
2205
BibRef
da Silva, F.G.[Fabiano G.],
Ramos, L.P.[Lucas P.],
Palm, B.G.[Bruna G.],
Machado, R.[Renato],
Assessment of Machine Learning Techniques for Oil Rig Classification
in C-Band SAR Images,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Qiao, Y.[Yiya],
Xi, X.H.[Xiao-Huan],
Nie, S.[Sheng],
Wang, P.[Pu],
Guo, H.[Hao],
Wang, C.[Cheng],
Power Pylon Reconstruction from Airborne LiDAR Data Based on
Component Segmentation and Model Matching,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link
2210
BibRef
Wu, B.L.[Bao-Long],
Wang, H.N.[Hao-Nan],
Chen, J.L.[Jian-Lai],
Feature Enhancement Using Multi-Baseline SAR
Interferometry-Correlated Synthesis Images for Power Transmission
Tower Detection in Mountain Layover Area,
RS(15), No. 15, 2023, pp. xx-yy.
DOI Link
2308
BibRef
Zhang, Y.[Yu],
Bai, L.[Lu],
Wang, Z.B.[Zhi-Bao],
Fan, M.[Meng],
Jurek-Loughrey, A.[Anna],
Zhang, Y.Q.[Yu-Qi],
Zhang, Y.[Ying],
Zhao, M.[Man],
Chen, L.[Liangfu],
Oil Well Detection under Occlusion in Remote Sensing Images Using the
Improved YOLOv5 Model,
RS(15), No. 24, 2023, pp. 5788.
DOI Link
2401
Different, but similar structures.
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Liang, X.[Xiao],
Wang, J.L.[Jia-Li],
Xu, P.[Peidong],
Kong, Q.Y.[Qing-Yu],
Han, Z.[Zhaogang],
GDiPAYOLO: A Fault Detection Algorithm for UAV Power Inspection
Scenarios,
SPLetters(30), 2023, pp. 1577-1581.
IEEE DOI
2311
BibRef
Li, X.[Xuhui],
Li, Y.[Yongrong],
Chen, Y.M.[Yi-Ming],
Zhang, G.[Geng],
Liu, Z.J.[Zheng-Jun],
Deep Learning-Based Target Point Localization for UAV Inspection of
Point Cloud Transmission Towers,
RS(16), No. 5, 2024, pp. 817.
DOI Link
2403
BibRef
Yao, Y.Y.[Yi-Yang],
Wang, X.[Xue],
Zhou, G.Q.[Guo-Qing],
Wang, Q.[Qing],
A two-stage substation equipment classification method based on
dual-scale attention,
IET-IPR(18), No. 8, 2024, pp. 2144-2153.
DOI Link
2406
feature extraction, image classification,
image recognition, object detection
BibRef
Pleterski, Ž.[Žan],
Rak, G.[Gašper],
Kregar, K.[Klemen],
Determination of Chimney Non-Verticality from TLS Data Using RANSAC
Method,
RS(16), No. 23, 2024, pp. 4541.
DOI Link
2501
BibRef
Abdelfattah, R.[Rabab],
Wang, X.F.[Xiao-Feng],
Wang, S.[Song],
Ttpla: An Aerial-image Dataset for Detection and Segmentation of
Transmission Towers and Power Lines,
ACCV20(VI:601-618).
Springer DOI
2103
BibRef
Yang, Z.[Zhi],
Zhao, B.B.[Bin-Bin],
Ma, X.[Xiao],
Luo, M.[Meng],
Han, J.J.[Jia-Jia],
Si, W.G.[Wei-Guo],
Super Resolution Enhancement of Satellite Remote Sensing Images of
Transmission Tower Based on Multi-map Residual Network and Wavelet
Transform,
CVIDL20(16-20)
IEEE DOI
2102
convolutional neural nets, edge detection, feature extraction,
image enhancement, image resolution, image sampling,
edge enhancement
BibRef
Deidda, M.,
Pala, A.,
Sanna, G.,
Modelling A Cell Tower Using SFM: Automated Detection of Structural
Elements From Skeleton Extraction on A Point Cloud,
ISPRS20(B2:399-406).
DOI Link
2012
BibRef
Wu, Z.,
Wang, H.,
Yu, W.,
Xi, J.,
Lei, W.,
Tang, T.,
3d High-efficiency and High-precision Model-driven Modelling for Power
Transmission Tower,
SmartCityApp20(421-426).
DOI Link
2012
BibRef
Liu, L.,
Zhang, T.,
Zhao, K.,
Wiliem, A.,
Astin-Walmsley, K.,
Lovell, B.,
Deep Inspection: An Electrical Distribution Pole Parts Study VIA Deep
Neural Networks,
ICIP19(4170-4174)
IEEE DOI
1910
electrical distribution pole, integrated inspection system,
deep neural networks, object detection, imbalanced data classification
BibRef
Maeda, K.,
Takahashi, S.,
Ogawa, T.,
Haseyama, M.,
Automatic estimation of deterioration level on transmission towers
via deep extreme learning machine based on local receptive field,
ICIP17(2379-2383)
IEEE DOI
1803
Estimation, Feature extraction, Inspection, Machine learning,
Poles and towers, Training, Visualization,
transmission tower
BibRef
Cabello, F.C.[Frank C.],
Iano, Y.[Yuzo],
Arthur, R.[Rangel],
Dueñas, A.[Abel],
León, J.[Julio],
Caetano, D.G.[Diogo G.],
Automatic Detection of Utility Poles Using the Bag of Visual Words
Method for Different Feature Extractors,
CAIP17(II: 116-126).
Springer DOI
1708
BibRef
Pontecorvo, C.[Carmine],
Redding, N.J.[Nicholas J.],
Non-Periodic Translation Symmetry Detection Using Global Self
Similarity,
DICTA17(1-8)
IEEE DOI
1804
Multiple poles and shadows in aerial images.
correlation methods, image matching, object detection,
actual aerial imagery, approximate size, blobs, consistent regions,
Tensile stress
BibRef
Sharma, H.[Hrishikesh],
Vellaiappan, A.[Adithya],
Dutta, T.[Tanima],
Balamuralidhar, P.,
Image Analysis-Based Automatic Utility Pole Detection for Remote
Surveillance,
DICTA15(1-7)
IEEE DOI
1603
BibRef
And: A1, A3, A2, A4:
A Real-Time Framework for Detection of Long Linear Infrastructural
Objects in Aerial Imagery,
ICIAR15(71-81).
Springer DOI
1507
BibRef
And: A3, A1, A2, A4:
Image Analysis-Based Automatic Detection of Transmission Towers using
Aerial Imagery,
IbPRIA15(641-651).
Springer DOI
1506
autonomous aerial vehicles
BibRef
Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
Insulators on Power Lines, Transmission Towers, Pylons .