15.3.28 Road Signs, Traffic Signs

Swedish Trafic Signs,
Online2010
WWW Link. Dataset, Traffic Signs. BibRef 1000

Challenging Unreal and Real Environments for Traffic Sign Detection and Recognition,
Online2017 CURE-TSD and CURE-TSR
WWW Link.
WWW Link. Dataset, Traffic Signs. Dataset, CURE-TSR. Dataset, CURE-TSD. Real-world and synthesized video sequences with challenging conditions. In total, there are 5,733 video sequences and around 1.72 million frames. BibRef 1700

Kehtarnavaz, N., Griswold, N.C., Kang, D.S.,
Stop-Sign Recognition Based on Color-Shape Processing,
MVA(6), 1993, pp. 206-208. BibRef 9300

Ritter, W., Stein, F., and Janssen, R.,
Traffic sign recognition using colour information,
MathMod(22), No. 4-7, August-October 1995, 149-161.
Elsevier DOI BibRef 9508

Piccioli, G., de Micheli, E., Parodi, P., Campani, M.,
Robust Method for Road Sign Detection and Recognition,
IVC(14), No. 3, April 1996, pp. 209-223.
Elsevier DOI 9607
BibRef

Piccioli, G., de Micheli, E., Campani, M.,
A Robust Method for Road Sign Detection and Recognition,
ECCV94(A:493-500).
Springer DOI BibRef 9400

de la Escalera, A., and Moreno, L.,
Road traffic sign detection and classification,
IndEle(44), 1997, pp. 848-859. BibRef 9700

de la Escalera, A., Armingol, J.M., Mata, M.,
Traffic sign recognition and analysis for intelligent vehicles,
IVC(21), No. 3, March 2003, pp. 247-258.
Elsevier DOI 0301
BibRef

Collado, J.M., Hilario, C., de la Escalera, A., Armingol, J.M.,
Model based vehicle detection for intelligent vehicles,
IVS04(572-577).
IEEE DOI 0411
BibRef

Miura, J., Kanda, T., Nakatani, S., and Shirai, Y.,
An Active Vision System for On-line Traffic Sign Recognition,
IEICE(E85-D), No. 11, 2002, pp. 1784-1792.
PDF File. BibRef 0200

Miura, J., Kanda, T., and Shirai, Y.,
An Active Vision System for Real-Time Traffic Sign Recogntition,
ITS00(52-57), Dearborn, MI, Oct. 2000.
PDF File. BibRef 0010

Paclik, P.[Pavel], Novoviová, J., Pudil, P., Somol, P.,
Road Sign Classification using Laplace Kernel Classifier,
PRL(21), No. 13-14, December 2000, pp. 1165-1173.
PDF File. 0011
BibRef
Earlier: SCIA99(275-282).
PDF File. BibRef

Hsu, S.H.[Shih-Hung], Huang, C.L.[Chung-Lin],
Road sign detection and recognition using matching pursuit method,
IVC(19), No. 3, February 2001, pp. 119-129.
Elsevier DOI 0103
BibRef
Earlier: A2, A1:
Road Sign Interpretation Using Matching Pursuit Method,
ICPR00(Vol I: 329-333).
IEEE DOI 0009
BibRef

Laumeyer, R.A.[Robert Anthony], Retterath, J.E.[James Eugene],
System for automatically generating database of objects of interest by analysis of images recorded by moving vehicle,
US_Patent6,363,161, March 26, 2002.
WWW Link. BibRef 0203

Laumeyer, R.A.[Robert Anthony], Retterath, J.E.[James Eugene],
Method and apparatus for identifying objects depicted in a videostream,
US_Patent6,266,442, July 24, 2001.
WWW Link. BibRef 0107
And: US_Patent6,625,315, Sep 23, 2003
WWW Link. BibRef
And: US_Patent7,092,548, Aug 15, 2006
WWW Link. BibRef

Laumeyer, R.A.[Robert Anthony], Retterath, J.E.[James Eugene],
Method and apparatus for rapidly determining whether a digitized image frame contains an object of interest,
US_Patent6,449,384, September 10, 2002.
WWW Link. BibRef 0209

Laumeyer, R.A.[Robert Anthony], Retterath, J.E.[James Eugene],
Method and apparatus for generating a database of road sign images and positions,
US_Patent6,453,056, September 17, 2002.
WWW Link. BibRef 0209

Fang, C.Y., Fuh, C.S., Yen, P.S., Cherng, S., Chen, S.W.,
An automatic road sign recognition system based on a computational model of human recognition processing,
CVIU(96), No. 2, November 2004, pp. 237-268.
Elsevier DOI 0410
BibRef
Earlier: A1, A2, A5, A3, Only:
A road sign recognition system based on dynamic visual model,
CVPR03(I: 750-755).
IEEE DOI 0307
Extract spatial and temporal information from video. Neural network for perception. BibRef

Fang, C.Y., Fuh, C.S., and Chen, S.W.,
Detection and tracking of road signs,
PRIA(11), 2001, pp. 304-308. BibRef 0100

de la Escalera, A., Armingol, J.M., Pastor, J.M., Rodriguez, F.J.,
Visual sign information extraction and identification by deformable models for intelligent vehicles,
ITS(5), No. 2, June 2004, pp. 57-68.
IEEE Abstract. 0501
BibRef

Wu, J.P.[Jian-Ping], Tsai, Y.C.J.[Yi-Chang James],
Real-time Speed Limit Sign Recognition Based on Locally Adaptive Thresholding and Depth-First-Search,
PhEngRS(71), No. 4, April 2005, pp. 405-414. Recognizing speed limit signs from video and extract the values, support real-time road inventory data collection operations.
WWW Link. 0509
BibRef

Gao, X.W., Podladchikova, L.N., Shaposhnikov, D.G., Hong, K., Shevtsova, N.,
Recognition of traffic signs based on their colour and shape features extracted using human vision models,
JVCIR(17), No. 4, August 2006, pp. 675-685.
Elsevier DOI 0711
Transformation invariant recognition; Traffic signs recognition; Feature extraction BibRef

Paclik, P.[Pavel], Novovicova, J.[Jana], Duin, R.P.W.[Robert P.W.],
Building Road-Sign Classifiers Using a Trainable Similarity Measure,
ITS(7), No. 3, September 2006, pp. 309-321.
IEEE DOI 0609
BibRef
Earlier:
A Trainable Similarity Measure for Image Classification,
ICPR06(III: 391-394).
IEEE DOI 0609

See also Dissimilarity-based classification of spectra: computational issues. BibRef

Paclik, P.[Pavel], Verzakov, S., Duin, R.P.W.,
Multi-class extensions of the GLDB feature extraction algorithm for spectral data,
ICPR04(IV: 629-632).
IEEE DOI 0409
Generalized Local Discriminant Bases
See also Best-bases feature extraction algorithms for classification of hyperspectral data. BibRef

Koncar, A.[Alan], Janßen, H.[Holger], Halgamuge, S.[Saman],
Gabor wavelet similarity maps for optimising hierarchical road sign classifiers,
PRL(28), No. 2, 15 January 2007, pp. 260-267.
Elsevier DOI 0611
Gabor wavelets; Jets; Euclidean distance; Normalised scalar product; Hierarchical classifier; Gabor similarity maps BibRef

Maldonado-Bascon, S., Lafuente-Arroyo, S., Gil-Jimenez, P., Gomez-Moreno, H., Lopez-Ferreras, F.,
Road-Sign Detection and Recognition Based on Support Vector Machines,
ITS(8), No. 2, April 2007, pp. 264-278.
IEEE DOI 0706
BibRef

Maldonado-Bascón, S.[Saturnino], Acevedo-Rodríguez, J.[Javier], Lafuente-Arroyo, S.[Sergio], Fernndez-Caballero, A., Lopez-Ferreras, F.,
An optimization on pictogram identification for the road-sign recognition task using SVMs,
CVIU(114), No. 3, March 2010, pp. 373-383.
Elsevier DOI 1003
Road sign; Automatic traffic sign detection and recognition system (TSDRS); Classification; Support vector machines (SVMs) BibRef

Gómez-Moreno, H.[Hilario], Maldonado-Bascón, S.[Saturnino], Gil-Jiménez, P.[Pedro], Lafuente-Arroyo, S.[Sergio],
Goal Evaluation of Segmentation Algorithms for Traffic Sign Recognition,
ITS(11), No. 4, December 2010, pp. 917-930.
IEEE DOI 1101
BibRef

Gil-Jiménez, P.[Pedro], Maldonado-Bascón, S.[Saturnino], Gómez-Moreno, H.[Hilario], Lafuente-Arroyo, S.[Sergio], Acevedo-Rodríguez, J.[Javier],
Algebraic-Distance Minimization of Lines and Ellipses for Traffic Sign Shape Localization,
IbPRIA07(II: 540-547).
Springer DOI 0706
BibRef

Liu, Y.S.[Yi-Sheng], Duh, D.J.[Der-Jyh], Chen, S.Y.[Shu-Yuan], Liu, R.S.[Ru-Sheng], Hsieh, J.W.[Jun-Wei],
Scale and skew-invariant road sign recognition,
IJIST(17), No. 1, 2007, pp. 28-39.
DOI Link 0707
BibRef

Barnes, N.M., Zelinsky, A., Fletcher, L.S.,
Real-Time Speed Sign Detection Using the Radial Symmetry Detector,
ITS(9), No. 2, June 2008, pp. 322-332.
IEEE DOI 0806
BibRef
Earlier: A1, A2, Only:
Real-time radial symmetry for speed sign detection,
IVS04(566-571).
IEEE DOI 0411
BibRef

Ishida, H.[Hiroyuki], Takahashi, T.[Tomokazu], Ide, I.[Ichiro], Mekada, Y.[Yoshito], Murase, H.[Hiroshi],
Generation of Training Data by Degradation Models for Traffic Sign Symbol Recognition,
IEICE(E90-D), No. 8, August 2007, pp. 1134-1141.
DOI Link 0708
BibRef
Earlier:
Identification of degraded traffic sign symbols by a generative learning method,
ICPR06(I: 531-534).
IEEE DOI 0609
BibRef

Gao, X.H.[Xiao-Hong], Hong, K.[Kunbin], Passmore, P.[Peter], Podladchikova, L.N.[Lubov N.], Shaposhnikov, D.G.[Dmitry G.],
Colour Vision Model-Based Approach for Segmentation of Traffic Signs,
JIVP(2008), No. 2008, pp. xx-yy.
DOI Link 0804
BibRef

Baro, X., Escalera, S., Vitria, J., Pujol, O., Radeva, P.I.,
Traffic Sign Recognition Using Evolutionary Adaboost Detection and Forest-ECOC Classification,
ITS(10), No. 1, March 2009, pp. 113-126.
IEEE DOI 0903
BibRef

Escalera, S.[Sergio], Pujol, O.[Oriol], Radeva, P.I.[Petia I.],
Traffic sign recognition system with beta-correction,
MVA(21), No. 2, February 2010, pp. xx-yy.
Springer DOI 1002
All the usual problems, multi-object, occlusion, illumination, etc. Based on Error Correcting Output Codes (ECOC). Ensemble of binary classifiers. BibRef

Escalera, S., Baró, X., Pujol, O., Vitrià, J., Radeva, P.I.,
Traffic-Sign Recognition Systems,
SpringerNew-York, 2011. ISBN: 978-1-4471-2244-9
WWW Link. Buy this book: Traffic-Sign Recognition Systems (SpringerBriefs in Computer Science) 1111
BibRef

Prieto, M.S.[Miguel S.], Allen, A.R.[Alastair R.],
Using self-organising maps in the detection and recognition of road signs,
IVC(27), No. 6, 4 May 2009, pp. 673-683.
Elsevier DOI 0904
Road sign detection; Road sign recognition; Self-organising map BibRef

Tsai, L.W.[Luo-Wei], Hsieh, J.W.[Jun-Wei], Chuang, C.H., Tseng, Y.J.[Yun-Jung], Fan, K.C.[Kuo-Chin], Lee, C.C.,
Road sign detection using eigen colour,
IET-CV(2), No. 3, September 2008, pp. 164-177.
DOI Link 0905
BibRef

Tsai, L.W.[Luo-Wei], Tseng, Y.J.[Yun-Jung], Hsieh, J.W.[Jun-Wei], Fan, K.C.[Kuo-Chin], Li, J.J.[Jiun-Jie],
Road Sign Detection Using Eigen Color,
ACCV07(I: 169-179).
Springer DOI 0711
BibRef

Ruta, A.[Andrzej], Li, Y.M.[Yong-Min], Liu, X.H.[Xiao-Hui],
Real-time traffic sign recognition from video by class-specific discriminative features,
PR(43), No. 1, January 2010, pp. 416-430,.
Elsevier DOI 0909
BibRef
Earlier:
Towards Real-Time Traffic Sign Recognition by Class-Specific Discriminative Features,
BMVC07(xx-yy).
PDF File. 0709
Traffic sign recognition; Computer vision-based driver assistance; Discriminative local regions; Colour Distance Transform; Forward feature selection BibRef

Ruta, A.[Andrzej], Li, Y.M.[Yong-Min], Liu, X.H.[Xiao-Hui],
Robust Class Similarity Measure for Traffic Sign Recognition,
ITS(11), No. 4, December 2010, pp. 846-855.
IEEE DOI 1101
BibRef

Ruta, A.[Andrzej], Li, Y.M.[Yong-Min], Porikli, F.M.[Fatih M.], Watanabe, S.[Shintaro], Kage, H.[Hiroshi], Sumi, K.[Kazuhiko],
A New Approach for In-Vehicle Camera Traffic Sign Detection and Recognition,
MVA09(509-).
PDF File. 0905
BibRef

Ruta, A.[Andrzej], Porikli, F.M.[Fatih M.], Watanabe, S.[Shintaro], Li, Y.M.[Yong-Min],
In-vehicle camera traffic sign detection and recognition,
MVA(22), No. 2, March 2011, pp. 359-375.
WWW Link. 1103
BibRef

Ruta, A.[Andrzej], Li, Y.M.[Yong-Min],
Learning pairwise image similarities for multi-classification using Kernel Regression Trees,
PR(45), No. 4, April 2012, pp. 1396-1408.
Elsevier DOI 1112
Visual similarity; Learning from example pairs; Object recognition; Kernel Regression Trees BibRef

Khan, J.F., Bhuiyan, S.M.A., Adhami, R.R.,
Image Segmentation and Shape Analysis for Road-Sign Detection,
ITS(12), No. 1, March 2011, pp. 83-96.
IEEE DOI 1103
BibRef

Fleyeh, H.[Hasan], Bin Mumtaz, A.H.R.M.[Al-Hasanat R. M.],
Adaptive Shadow and Highlight Invariant Colour Segmentation for Traffic Sign Recognition Based on Kohonen SOM,
IJIS(20), No. 1, 2011.
DOI Link 1103
Pre publication info, check exact issue, page reference. BibRef

Fleyeh, H.[Hasan],
Traffic sign recognition by fuzzy sets,
IVS08(xx-yy). BibRef 0800

Fleyeh, H.[Hasan], Dougherty, M.,
Traffic sign classification using invariant features and Support Vector Machines,
IVS08(xx-yy). BibRef 0800
Earlier:
SVM Based Traffic Sign Classification Using Legendre Moments,
IICAI07(xx-yy). BibRef
Earlier:
Road and traffic sign detection and recognition,
EWGT05(xx-yy). Poznan, Poland, 13-16 September, 2005. BibRef

Fleyeh, H.[Hasan], Gilani, S., Dougherty, M.,
Road Sign Detection and Recognition Using A Fuzzy ARTMAP: A Case Study Swedish Speed-Limit Signs,
AI Soft Computing06(xx-yy). Palma de Mallorca, Spain, 28-30 August, 2006. BibRef 0608

Fleyeh, H.[Hasan], and Davami, E.[Erfan],
Eigen-Based Traffic Sign Recognition,
IET-ITS(5), No. 3, 2011, pp. 190-196.
WWW Link. BibRef 1100

Fleyeh, H., Biswas, R., and Bhuiyan, N.,
An Adaptive Approach to Detect Warning Traffic Signs Using SOM and Windowed Hough Transform,
SIPA11(xx-yy), June 22-24, 2011, Crete. BibRef 1106

Fleyeh, H.[Hasan], Dougherty, M., Aenugula, D., Baddam, S.,
Invariant Road Sign Recognition with Fuzzy ARTMAP and Zernike Moments,
IVS07(xx-yy). BibRef 0700

Fleyeh, H.[Hasan], Shi, M., Wu, H.,
A Robust Model for Traffic Signs Recognition Based on Support Vector Machines,
CISP08(xx-yy). BibRef 0800
And:
Support vector machines for traffic signs recognition,
IJCNN08(xx-yy). BibRef

Fleyeh, H.[Hasan], Zhao, P.,
A Contour-based Separation of Vertically Attached Traffic Signs,
IECON08(xx-yy). Orlando, FL, 2008 BibRef 0800

Fleyeh, H.[Hasan],
Shadow and Highlight Invariant Colour Segmentation Algorithm for Traffic Signs,
CIS06(xx-yy). Bangkok, Thailand, June, 2006. BibRef 0606
Earlier:
Traffic Signs Color Detection and Segmentation in Poor Light Conditions,
MVA05(xx-yy). BibRef
And:
Road and Traffic Sign Color Detection and Segmentation: A Fuzzy Approach,
MVA05(xx-yy) BibRef
And:
A Novel Fuzzy Approach For Shape Determination of Traffic Signs,
IICAI05(xx-yy). BibRef
Earlier:
Color detection and segmentation for road and traffic signs,
CIS04(xx-yy). Singapore, December, 2004. BibRef

Gonzalez, Á., Garrido, M.A., Fernandez Llorca, D., Gavilan, M., Fernandez, J.P., Alcantarilla, P.F., Parra, I., Herranz, F., Bergasa, L.M., Sotelo, M.A., Revenga de Toro, P.,
Automatic Traffic Signs and Panels Inspection System Using Computer Vision,
ITS(12), No. 2, June 2011, pp. 485-499.
IEEE DOI 1101
BibRef

Larsson, F.[Fredrik], Felsberg, M.[Michael], Forssen, P.E.[Per-Erik],
Correlating fourier descriptors of local patches for road sign recognition,
IET-CV(5), No. 4, 2011, pp. 244-254.
DOI Link 1107
BibRef
Earlier: A1, A2, Only:
Using Fourier Descriptors and Spatial Models for Traffic Sign Recognition,
SCIA11(238-249).
Springer DOI 1105
BibRef

Meuter, M., Nunn, C., Gormer, S.M., Muller-Schneiders, S., Kummert, A.,
A Decision Fusion and Reasoning Module for a Traffic Sign Recognition System,
ITS(12), No. 4, December 2011, pp. 1126-1134.
IEEE DOI 1112
BibRef

Xu, S.,
Robust traffic sign shape recognition using geometric matching,
IET-ITS(3), No. 1, 2009, pp. 10-18.
DOI Link 1204
BibRef

McLoughlin, S., Deegan, C., Mulvihill, C., Fitzgerald, C., Markham, C.,
Mobile mapping for the automated analysis of road signage and delineation,
IET-ITS(2), No. 1, 2008, pp. 61-73.
DOI Link 1204
BibRef

Murray, S., Haughey, S., Brogan, M., Fitzgerald, C., McLoughlin, S., Deegan, C.,
Mobile mapping system for the automated detection and analysis of road delineation,
IET-ITS(5), No. 4, 2011, pp. 221-230.
DOI Link 1204
BibRef

Gu, Y.[Yanlei], Panahpour Tehrani, M.[Mehrdad], Yendo, T.[Tomohiro], Fujii, T.[Toshiaki], Tanimoto, M.[Masayuki],
Traffic Sign Recognition with Invariance to Lighting in Dual-Focal Active Camera System,
IEICE(E95-D), No. 7, July 2012, pp. 1775-1790.
WWW Link. 1208
BibRef

Zhang, K.[Ka], Sheng, Y.[Yehua], Li, J.,
Automatic detection of road traffic signs from natural scene images based on pixel vector and central projected shape feature,
IET-ITS(6), No. 2, 2012, pp. 282-291.
DOI Link 1209
BibRef

Zhang, K.[Ka], Sheng, Y.[Yehua], Wang, P.[Peifang], Luo, L.[Lin], Ye, C.[Chun], Gong, Z.J.[Zhi-Jun],
Automatic Recognition of Traffic Signs in Natural Scene Image Based on Central Projection Transformation,
ISPRS08(B3b: 627 ff).
PDF File. 0807
BibRef

Cavegn, S.[Stefan], Nebiker, S.[Stephan],
Automated 3D Road Sign Mapping with Stereovision-based Mobile Mapping exploiting Depth Information from Dense Stereo Matching,
PFG(2012), No. 5, 2012, pp. 631-645.
WWW Link. 1211
BibRef
Earlier:
Automated 3d Road Sign Mapping With Stereovision-based Mobile Mapping Exploiting Disparity Information From Dense Stereo Matching,
ISPRS12(XXXIX-B4:61-66).
DOI Link 1209
BibRef

Nebiker, S., Cavegn, S., Eugster, H., Laemmer, K., Markram, J., Wagner, R.,
Fusion of Airborne and Terrestrial Image-based 3D Modelling for Road Infrastructure Management: Vision and First Experiments,
ISPRS12(XXXIX-B4:79-84).
DOI Link 1209
BibRef

Lu, K., Ding, Z., Ge, S.,
Sparse-Representation-Based Graph Embedding for Traffic Sign Recognition,
ITS(13), No. 4, December 2012, pp. 1515-1524.
IEEE DOI 1212
BibRef

Zaklouta, F., Stanciulescu, B.,
Real-Time Traffic-Sign Recognition Using Tree Classifiers,
ITS(13), No. 4, December 2012, pp. 1507-1514.
IEEE DOI 1212
BibRef

Greenhalgh, J., Mirmehdi, M.,
Real-Time Detection and Recognition of Road Traffic Signs,
ITS(13), No. 4, December 2012, pp. 1498-1506.
IEEE DOI 1212
BibRef

Greenhalgh, J., Mirmehdi, M.,
Recognizing Text-Based Traffic Signs,
ITS(16), No. 3, June 2015, pp. 1360-1369.
IEEE DOI 1506
Cameras BibRef

Mogelmose, A., Trivedi, M.M., Moeslund, T.B.,
Vision-Based Traffic Sign Detection and Analysis for Intelligent Driver Assistance Systems: Perspectives and Survey,
ITS(13), No. 4, December 2012, pp. 1484-1497.
IEEE DOI 1212
BibRef

Philipsen, M.P., Jensen, M.B., Trivedi, M.M., Mogelmose, A.[Andreas], Moeslund, T.B.[Thomas B.],
Ongoing work on traffic lights: Detection and evaluation,
AVSS15(1-6)
IEEE DOI 1511
image sensors BibRef

Mogelmose, A.[Andreas], Trivedi, M.M.[Mohan M.], Moeslund, T.B.[Thomas B.],
Learning to detect traffic signs: Comparative evaluation of synthetic and real-world datasets,
ICPR12(3452-3455).
WWW Link. 1302
BibRef

Stallkamp, J., Schlipsing, M., Salmen, J., Igel, C.,
Introduction to the Special Issue on Machine Learning for Traffic Sign Recognition,
ITS(13), No. 4, December 2012, pp. 1481-1483.
IEEE DOI 1212
BibRef

Pei, D.L.[De-Li], Sun, F.C.[Fu-Chun], Liu, H.P.[Hua-Ping],
Supervised Low-Rank Matrix Recovery for Traffic Sign Recognition in Image Sequences,
SPLetters(20), No. 3, March 2013, pp. 241-244.
IEEE DOI 1303
BibRef

Soheilian, B.[Bahman], Paparoditis, N.[Nicolas], Vallet, B.[Bruno],
Detection and 3D reconstruction of traffic signs from multiple view color images,
PandRS(77), No. 1, March 2013, pp. 1-20.
Elsevier DOI 1303
Traffic sign; Color segmentation; Geometric shape estimation; Template matching; Constrained multi-view reconstruction BibRef

Yan, W.Y.[Wai Yeung], Shaker, A., Easa, S.,
Potential Accuracy of Traffic Signs' Positions Extracted From Google Street View,
ITS(14), No. 2, 2013, pp. 1011-1016.
IEEE DOI 1307
traffic engineering computing; ground control points; traffic sign position BibRef

Munoz-Organero, M., Magana, V.C.,
Validating the Impact on Reducing Fuel Consumption by Using an EcoDriving Assistant Based on Traffic Sign Detection and Optimal Deceleration Patterns,
ITS(14), No. 2, 2013, pp. 1023-1028.
IEEE DOI 1307
Fuel optimal control BibRef

Boumediene, M.[Mohammed], Cudel, C.[Christophe], Basset, M.[Michel], Ouamri, A.[Abdelaziz],
Triangular traffic signs detection based on RSLD algorithm,
MVA(24), No. 8, November 2013, pp. 1721-1732.
Springer DOI 1310
BibRef

Zhang, Q.S.[Qie-Shi], Kamata, S.I.[Sei-Ichiro],
Improved Color Barycenter Model and Its Separation for Road Sign Detection,
IEICE(E96-D), No. 12, December 2013, pp. 2839-2849.
WWW Link. 1312
BibRef
Earlier:
Automatic road sign detection method based on Color Barycenters Hexagon model,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Souani, C.[Chokri], Faiedh, H.[Hassene], Besbes, K.[Kamel],
Efficient algorithm for automatic road sign recognition and its hardware implementation,
RealTimeIP(9), No. 1, March 2014, pp. 79-93.
WWW Link. 1403
BibRef

Timofte, R.[Radu], Zimmermann, K.[Karel], Van Gool, L.J.[Luc J.],
Multi-view traffic sign detection, recognition, and 3D localisation,
MVA(25), No. 3, April 2014, pp. 633-647.
WWW Link. 1404
BibRef
Earlier: WACV09(1-8).
IEEE DOI 0912
BibRef

Timofte, R.[Radu], Van Gool, L.J.[Luc J.],
Multi-view manhole detection, recognition, and 3D localisation,
CVRSE11(188-195).
IEEE DOI 1201
BibRef

Šegvic, S.[Siniša], Brkic, K.[Karla], Kalafatic, Z.[Zoran], Pinz, A.[Axel],
Exploiting temporal and spatial constraints in traffic sign detection from a moving vehicle,
MVA(25), No. 3, April 2014, pp. 649-665.
WWW Link. 1404
BibRef

Brkic, K.[Karla], Pinz, A.[Axel], Kalafatic, Z.[Zoran], Šegvic, S.[Siniša],
Towards Space-Time Semantics in Two Frames,
ARTEMIS12(III: 121-130).
Springer DOI 1210
BibRef

Brkic, K.[Karla], Pinz, A.[Axel], Šegvic, S.[Siniša], Kalafatic, Z.[Zoran],
Histogram-Based Description of Local Space-Time Appearance,
SCIA11(206-217).
Springer DOI 1105
BibRef

Brkic, K., Segvic, S., Kalafatic, Z., Sikiric, I., Pinz, A.,
Generative modeling of spatio-temporal traffic sign trajectories,
UCVP10(25-31).
IEEE DOI 1006
BibRef

Overett, G.[Gary], Tychsen-Smith, L.[Lachlan], Petersson, L.[Lars], Pettersson, N.[Niklas], Andersson, L.[Lars],
Creating robust high-throughput traffic sign detectors using centre-surround HOG statistics,
MVA(25), No. 3, April 2014, pp. 713-726.
Springer DOI 1404
BibRef

Wang, G.Y.[Gang-Yi], Ren, G.H.[Guang-Hui], Jiang, L.H.[Li-Hui], Quan, T.F.[Tai-Fan],
Hole-based traffic sign detection method for traffic signs with red rim,
VC(30), No. 5, May 2014, pp. 539-551.
WWW Link. 1404
BibRef

Hazelhoff, L.[Lykele], Creusen, I.M.[Ivo M.], de With, P.H.N.[Peter H.N.],
Exploiting street-level panoramic images for large-scale automated surveying of traffic signs,
MVA(25), No. 7, October 2014, pp. 1893-1911.
WWW Link. 1410
BibRef
Earlier:
System for semi-automated surveying of street-lighting poles from street-level panoramic images,
WACV14(129-136)
IEEE DOI 1406
Detectors BibRef

Xu, D.[Dan], Xu, W.[Wei], Tang, Z.M.[Zhen-Min], Liu, F.[Fan],
Exploiting Visual Saliency and Bag-of-Words for Road Sign Recognition,
IEICE(E97-D), No. 9, September 2014, pp. 2473-2482.
WWW Link. 1410
BibRef

Yuan, X.[Xue], Hao, X.L.[Xiao-Li], Chen, H.J.[Hou-Jin], Wei, X.[Xueye],
Robust Traffic Sign Recognition Based on Color Global and Local Oriented Edge Magnitude Patterns,
ITS(15), No. 4, August 2014, pp. 1466-1477.
IEEE DOI 1410
affine transforms BibRef

Yuan, X.[Xue], Guo, J., Hao, X.L.[Xiao-Li], Chen, H.J.[Hou-Jin],
Traffic Sign Detection via Graph-Based Ranking and Segmentation Algorithms,
SMCS(45), No. 12, December 2015, pp. 1509-1521.
IEEE DOI 1512
Image color analysis BibRef

Lee, D.J.[Dong-Jin], Yoon, H.[Hosub], Chung, M.A.[Myung-Ae], Kim, J.[Jaehong],
Robust Sign Recognition System at Subway Stations Using Verification Knowledge,
ERRI(36), No. 5, October 2014, pp. 696-703.
DOI Link 1410
For pedestrians in subway stations. BibRef

Jin, J.Q.[Jun-Qi], Fu, K.[Kun], Zhang, C.S.[Chang-Shui],
Traffic Sign Recognition With Hinge Loss Trained Convolutional Neural Networks,
ITS(15), No. 5, October 2014, pp. 1991-2000.
IEEE DOI 1410
gradient methods BibRef

Liu, C.S.[Chun-Sheng], Chang, F.L.[Fa-Liang], Chen, Z.X.[Zhen-Xue],
Rapid Multiclass Traffic Sign Detection in High-Resolution Images,
ITS(15), No. 6, December 2014, pp. 2394-2403.
IEEE DOI 1412
image colour analysis BibRef

Boumediene, M., Lauffenburger, J.P., Daniel, J., Cudel, C., Ouamri, A.,
Multi-ROI Association and Tracking With Belief Functions: Application to Traffic Sign Recognition,
ITS(15), No. 6, December 2014, pp. 2470-2479.
IEEE DOI 1412
Kalman filters BibRef

Salti, S.[Samuele], Petrelli, A.[Alioscia], Tombari, F.[Federico], Fioraio, N.[Nicola], di Stefano, L.[Luigi],
Traffic sign detection via interest region extraction,
PR(48), No. 4, 2015, pp. 1039-1049.
Elsevier DOI 1502
Mobile mapping BibRef

Mogelmose, A., Liu, D., Trivedi, M.M.,
Detection of U.S. Traffic Signs,
ITS(16), No. 6, December 2015, pp. 3116-3125.
IEEE DOI 1512
Advanced driver assistance systems BibRef

Wen, C., Li, J., Luo, H., Yu, Y., Cai, Z., Wang, H., Wang, C.,
Spatial-Related Traffic Sign Inspection for Inventory Purposes Using Mobile Laser Scanning Data,
ITS(17), No. 1, January 2016, pp. 27-37.
IEEE DOI 1601
Feature extraction BibRef

You, C., Wen, C., Wang, C., Li, J., Habib, A.,
Joint 2-D-3-D Traffic Sign Landmark Data Set for Geo-Localization Using Mobile Laser Scanning Data,
ITS(20), No. 7, July 2019, pp. 2550-2565.
IEEE DOI 1907
Semantics, Trajectory, Machine learning, Shape, Autonomous vehicles, Estimation, geo-localization BibRef

Liu, C., Chang, F., Chen, Z., Liu, D.,
Fast Traffic Sign Recognition via High-Contrast Region Extraction and Extended Sparse Representation,
ITS(17), No. 1, January 2016, pp. 79-92.
IEEE DOI 1601
Accuracy BibRef

Yu, Y.T.[Yong-Tao], Li, J.[Jonathan], Wen, C.L.[Cheng-Lu], Guan, H.Y.[Hai-Yan], Luo, H.[Huan], Wang, C.[Cheng],
Bag-of-visual-phrases and hierarchical deep models for traffic sign detection and recognition in mobile laser scanning data,
PandRS(113), No. 1, 2016, pp. 106-123.
Elsevier DOI 1602
Bag-of-visual-phrases BibRef

Huang, P.D.[Peng-Di], Cheng, M.[Ming], Chen, Y.P.[Yi-Ping], Luo, H.[Huan], Wang, C.[Cheng], Li, J.[Jonathan],
Traffic Sign Occlusion Detection Using Mobile Laser Scanning Point Clouds,
ITS(18), No. 9, September 2017, pp. 2364-2376.
IEEE DOI 1709
object detection, optical scanners, road traffic, stereo image processing, traffic engineering computing, 3D point clouds, RIEGL VMX-450 system,
See also Marked Point Process for Automated Tree Detection from Mobile Laser Scanning Point Cloud Data, A.
See also Automated Detection of Three-Dimensional Cars in Mobile Laser Scanning Point Clouds Using DBM-Hough-Forests. BibRef

Guan, H.Y.[Hai-Yan], Yu, Y.T.[Yong-Tao], Li, D.L.[Di-Long], Li, J.[Jonathan],
Automatic Traffic Sign Detection and Recognition Using Mobile Lidar Data with Digital Images,
ISPRS20(B3:599-603).
DOI Link 2012
BibRef

Soilán, M.[Mario], Riveiro, B.[Belén], Martínez-Sánchez, J.[Joaquín], Arias, P.[Pedro],
Traffic sign detection in MLS acquired point clouds for geometric and image-based semantic inventory,
PandRS(114), No. 1, 2016, pp. 92-101.
Elsevier DOI 1604
Mobile mapping BibRef

Tan, M., Wang, B., Wu, Z., Wang, J., Pan, G.,
Weakly Supervised Metric Learning for Traffic Sign Recognition in a LIDAR-Equipped Vehicle,
ITS(17), No. 5, May 2016, pp. 1415-1427.
IEEE DOI 1605
Image recognition BibRef

Liu, C., Chang, F., Liu, C.,
Occlusion-robust traffic sign detection via cascaded colour cubic feature,
IET-ITS(10), No. 5, 2016, pp. 354-360.
DOI Link 1608
computer vision BibRef

Hu, Z., Li, N.,
Vision-based position computation from in-vehicle video log images for road sign inventory,
IET-ITS(10), No. 6, 2016, pp. 414-420.
DOI Link 1608
approximation theory BibRef

Yang, Y., Luo, H., Xu, H., Wu, F.,
Towards Real-Time Traffic Sign Detection and Classification,
ITS(17), No. 7, July 2016, pp. 2022-2031.
IEEE DOI 1608
feature extraction BibRef

Hou, Y.L., Hao, X., Chen, H.,
A Cognitively Motivated Method for Classification of Occluded Traffic Signs,
SMCS(47), No. 2, February 2017, pp. 255-262.
IEEE DOI 1702
cognition BibRef

Huang, Z., Yu, Y., Gu, J., Liu, H.,
An Efficient Method for Traffic Sign Recognition Based on Extreme Learning Machine,
Cyber(47), No. 4, April 2017, pp. 920-933.
IEEE DOI 1704
Computational efficiency BibRef

Lu, X., Wang, Y., Zhou, X., Zhang, Z., Ling, Z.,
Traffic Sign Recognition via Multi-Modal Tree-Structure Embedded Multi-Task Learning,
ITS(18), No. 4, April 2017, pp. 960-972.
IEEE DOI 1704
Benchmark testing BibRef

Aghdam, H.H.[Hamed Habibi], Heravi, E.J.[Elnaz Jahani], Puig, D.[Domenec],
A Practical and Highly Optimized Convolutional Neural Network for Classifying Traffic Signs in Real-Time,
IJCV(122), No. 2, April 2017, pp. 246-269.
Springer DOI 1704
BibRef
Earlier:
Fusing Convolutional Neural Networks with a Restoration Network for Increasing Accuracy and Stability,
CVRoads16(I: 178-191).
Springer DOI 1611
BibRef

Zeng, Y., Xu, X., Shen, D., Fang, Y., Xiao, Z.,
Traffic Sign Recognition Using Kernel Extreme Learning Machines With Deep Perceptual Features,
ITS(18), No. 6, June 2017, pp. 1647-1653.
IEEE DOI 1706
Color, Computational efficiency, Feature extraction, Image color analysis, Kernel, Neural networks, Training, Traffic sign recognition, color space, convolutional neural network, extreme learning machine, kernel, lab Comments:
See also Comments on Traffic Sign Recognition Using Kernel Extreme Learning Machines With Deep Perceptual Features. BibRef

Zeng, Y.,
Reply to 'Comments on Traffic Sign Recognition Using Kernel Extreme Learning Machines With Deep Perceptual Features',
ITS(20), No. 10, October 2019, pp. 3762-3764.
IEEE DOI 1910
Kernel, Training, Complexity theory, Computational efficiency, Computational modeling, Convolutional neural networks, deep learning BibRef

Jain, S., Singhal, M., Shukla, S.,
Comments on 'Traffic Sign Recognition Using Kernel Extreme Learning Machines With Deep Perceptual Features',
ITS(20), No. 10, October 2019, pp. 3759-3761.
IEEE DOI 1910
Mathematical model, Kernel, Training, Computational modeling, Computational complexity, Feature extraction, kernel matrix
See also Traffic Sign Recognition Using Kernel Extreme Learning Machines With Deep Perceptual Features.
See also Reply to Comments on Traffic Sign Recognition Using Kernel Extreme Learning Machines With Deep Perceptual Features. BibRef

Yuan, Y., Xiong, Z., Wang, Q.,
An Incremental Framework for Video-Based Traffic Sign Detection, Tracking, and Recognition,
ITS(18), No. 7, July 2017, pp. 1918-1929.
IEEE DOI 1706
Color, Detectors, Image color analysis, Machine learning, Shape, Target tracking, ITS, Machine learning, detection, incremental learning, recognition, tracking, traffic, sign BibRef

Yuan, Y., Xiong, Z., Wang, Q.,
VSSA-NET: Vertical Spatial Sequence Attention Network for Traffic Sign Detection,
IP(28), No. 7, July 2019, pp. 3423-3434.
IEEE DOI 1906
feature extraction, image classification, learning (artificial intelligence), object detection, sequence attention model BibRef

Rehman, Y.[Yawar], Riaz, I.[Irfan], Fan, X.[Xue], Shin, H.[Hyunchul],
D-patches: effective traffic sign detection with occlusion handling,
IET-CV(11), No. 5, August 2017, pp. 368-377.
DOI Link 1707
Type: Article BibRef

Gudigar, A.[Anjan], Chokkadi, S.[Shreesha], Raghavendra, U., Acharya, U.R.[U. Rajendra],
Local texture patterns for traffic sign recognition using higher order spectra,
PRL(94), No. 1, 2017, pp. 202-210.
Elsevier DOI 1708
Entropy BibRef

Saadna, Y.[Yassmina], Behloul, A.[Ali],
An overview of traffic sign detection and classification methods,
MultInfoRetr(6), No. 3, September 2017, pp. 193-210.
Springer DOI 1708
Survey, Traffic Signs. BibRef

Tsai, C.Y.[Chi-Yi], Liao, H.C.[Hsien-Chen], Hsu, K.J.[Kuang-Jui],
Real-time embedded implementation of robust speed-limit sign recognition using a novel centroid-to-contour description method,
IET-CV(11), No. 6, September 2017, pp. 407-414.
DOI Link 1709
BibRef

Zhu, Z., Lu, J., Martin, R.R., Hu, S.,
An Optimization Approach for Localization Refinement of Candidate Traffic Signs,
ITS(18), No. 11, November 2017, pp. 3006-3016.
IEEE DOI 1711
Benchmark testing, Detectors, Feature extraction, Image color analysis, Image segmentation, Shape, Standards, Traffic sign localization, graph cut, optimization BibRef

Wang, D., Hou, X., Xu, J., Yue, S., Liu, C.L.,
Traffic Sign Detection Using a Cascade Method With Fast Feature Extraction and Saliency Test,
ITS(18), No. 12, December 2017, pp. 3290-3302.
IEEE DOI 1712
Color, Detectors, Feature extraction, Image color analysis, Shape, Support vector machines, Traffic sign detection, cascade system, saliency test BibRef

Zhu, Y., Liao, M., Yang, M., Liu, W.,
Cascaded Segmentation-Detection Networks for Text-Based Traffic Sign Detection,
ITS(19), No. 1, January 2018, pp. 209-219.
IEEE DOI 1801
Assistive technology, Character recognition, Detectors, Machine learning, Text recognition, Text detection, textboxes BibRef

Zhang, J., Hui, L., Lu, J., Zhu, Y.,
Attention-based Neural Network for Traffic Sign Detection,
ICPR18(1839-1844)
IEEE DOI 1812
Object detection, Feature extraction, Task analysis, Training, Adaptation models, Convolutional neural networks BibRef

Temel, D., Al Regib, G.,
Traffic Signs in the Wild: Highlights from the IEEE Video and Image Processing Cup 2017 Student Competition,
SPMag(35), No. 2, March 2018, pp. 154-161.
IEEE DOI 1804
[SP Competitions] BibRef

Luo, H., Yang, Y., Tong, B., Wu, F., Fan, B.,
Traffic Sign Recognition Using a Multi-Task Convolutional Neural Network,
ITS(19), No. 4, April 2018, pp. 1100-1111.
IEEE DOI 1804
Cameras, Computational efficiency, Feature extraction, Image color analysis, Image recognition, Neural networks, traffic sign classification BibRef

Dai, H.M.[Hui-Ming], Zhang, X.[Xin], Yang, D.C.[Da-Cheng],
Road traffic sign recognition algorithm based on computer vision,
IJCVR(8), No. 1, 2018, pp. 85-93.
DOI Link 1804
BibRef

Lee, H.S., Kim, K.,
Simultaneous Traffic Sign Detection and Boundary Estimation Using Convolutional Neural Network,
ITS(19), No. 5, May 2018, pp. 1652-1663.
IEEE DOI 1805
Estimation, Feature extraction, Image color analysis, Object detection, Robustness, Shape, traffic sign boundary estimation BibRef

Li, F.S.[Fa-Shuai], Oude Elberink, S.[Sander], Vosselman, G.[George],
Pole-Like Road Furniture Detection and Decomposition in Mobile Laser Scanning Data Based on Spatial Relations,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link 1805
BibRef

Oude Elberink, S.[Sander], Khoshelham, K.[Kourosh],
Automatic Extraction of Railroad Centerlines from Mobile Laser Scanning Data,
RS(7), No. 5, 2015, pp. 5565-5583.
DOI Link 1506
BibRef

Li, F.[Fashuai], Lehtomäki, M.[Matti], Oude Elberink, S.[Sander], Vosselman, G.[George], Kukko, A.[Antero], Puttonen, E.[Eetu], Chen, Y.W.[Yu-Wei], Hyyppä, J.[Juha],
Semantic segmentation of road furniture in mobile laser scanning data,
PandRS(154), 2019, pp. 98-113.
Elsevier DOI 1907
Pole-like road furniture, Interpretation, Decomposition, Machine learning classifiers, Mobile laser scanning BibRef

Li, F.[Fashuai], Zhou, Z.[Zhize], Xiao, J.H.[Jian-Hua], Chen, R.Z.[Rui-Zhi], Lehtomäki, M.[Matti], Oude Elberink, S.[Sander], Vosselman, G.[George], Hyyppä, J.[Juha], Chen, Y.W.[Yu-Wei], Kukko, A.[Antero],
Instance-Aware Semantic Segmentation of Road Furniture in Mobile Laser Scanning Data,
ITS(23), No. 10, October 2022, pp. 17516-17529.
IEEE DOI 2210
Roads, Point cloud compression, Semantics, Machine learning, Feature extraction, Shape, pole-like road furniture BibRef

Maanpää, J.[Jyri], Melekhov, I.[Iaroslav], Taher, J.[Josef], Manninen, P.[Petri], Hyyppä, J.[Juha],
Leveraging Road Area Semantic Segmentation with Auxiliary Steering Task,
CIAP22(I:727-738).
Springer DOI 2205
BibRef

Hmida, R.[Rihab], Ben Abdelali, A.[Abdessalem], Mtibaa, A.[Abdellatif],
Hardware implementation and validation of a traffic road sign detection and identification system,
RealTimeIP(15), No. 1, June 2018, pp. 13-30.
Springer DOI 1806
BibRef

Natarajan, S.[Sudha], Annamraju, A.K.[Abhishek Kumar], Baradkar, C.S.[Chaitree Sham],
Traffic sign recognition using weighted multi-convolutional neural network,
IET-ITS(12), No. 10, December 2018, pp. 1396-1405.
DOI Link 1812
BibRef

Rehman, Y.[Yawar], Khan, J.A.[Jameel Ahmed], Shin, H.[Hyunchul],
Efficient coarser-to-fine holistic traffic sign detection for occlusion handling,
IET-IPR(12), No. 12, December 2018, pp. 2229-2237.
DOI Link 1812
BibRef

Khalid, S.[Sara], Muhammad, N.[Nazeer], Sharif, M.[Muhammad],
Automatic measurement of the traffic sign with digital segmentation and recognition,
IET-ITS(13), No. 2, February 2019, pp. 269-279.
DOI Link 1902
BibRef

Li, Y.[You], Wang, W.X.[Wei-Xi], Tang, S.J.[Sheng-Jun], Li, D.L.[Da-Lin], Wang, Y.K.[Yan-Kun], Yuan, Z.L.[Zhi-Lu], Guo, R.Z.[Ren-Zhong], Li, X.M.[Xiao-Ming], Xiu, W.Q.[Wen-Qun],
Localization and Extraction of Road Poles in Urban Areas from Mobile Laser Scanning Data,
RS(11), No. 4, 2019, pp. xx-yy.
DOI Link 1903
BibRef

Li, J., Wang, Z.,
Real-Time Traffic Sign Recognition Based on Efficient CNNs in the Wild,
ITS(20), No. 3, March 2019, pp. 975-984.
IEEE DOI 1903
Task analysis, Image color analysis, Databases, Shape, Detectors, Real-time systems, Proposals, Traffic sign recognition, efficient CNN BibRef

Guo, D., Zhu, L., Lu, Y., Yu, H., Wang, S.,
Small Object Sensitive Segmentation of Urban Street Scene With Spatial Adjacency Between Object Classes,
IP(28), No. 6, June 2019, pp. 2643-2653.
IEEE DOI 1905
image classification, image segmentation, learning (artificial intelligence), object detection, urban street scene BibRef

Javanmardi, M.[Mohammadreza], Song, Z.Q.[Zi-Qi], Qi, X.J.[Xiao-Jun],
Automated traffic sign and light pole detection in mobile LiDAR scanning data,
IET-ITS(13), No. 5, May 2019, pp. 803-815.
DOI Link 1906
BibRef

Luo, X.P.[Xiao-Ping], Zhu, J.H.[Jin-Hao], Yu, Q.Y.[Qing-Ying],
Efficient convNets for fast traffic sign recognition,
IET-ITS(13), No. 6, June 2019, pp. 1011-1015.
DOI Link 1906
BibRef

Zhang, S.X.[Shan-Xin], Wang, C.[Cheng], Lin, L.[Lili], Wen, C.L.[Cheng-Lu], Yang, C.H.[Chen-Hui], Zhang, Z.[Zhemin], Li, J.[Jonathan],
Automated Visual Recognizability Evaluation of Traffic Sign Based on 3D LiDAR Point Clouds,
RS(11), No. 12, 2019, pp. xx-yy.
DOI Link 1907
BibRef

Zhang, S.X.[Shan-Xin], Wang, C.[Cheng], Cheng, M., Li, J.[Jonathan],
Automated Visibility Field Evaluation of Traffic Sign Based On 3d Lidar Point Clouds,
Laser19(1185-1190).
DOI Link 1912
BibRef

Li, C., Chen, Z., Wu, Q.M.J., Liu, C.,
Deep Saliency With Channel-Wise Hierarchical Feature Responses for Traffic Sign Detection,
ITS(20), No. 7, July 2019, pp. 2497-2509.
IEEE DOI 1907
Feature extraction, Visualization, Image color analysis, Convolutional neural networks, Saliency detection, Kernel, Shape, traffic sign detection BibRef

Zhang, Y., Yang, J., Zhang, H., Hwang, J.,
Bundle Adjustment for Monocular Visual Odometry Based on Detected Traffic Sign Features,
ICIP19(4350-4354)
IEEE DOI 1910
traffic sign, bundle adjustment, visual odometry, pose estimation, optimization BibRef

Farhat, W.[Wajdi], Faiedh, H.[Hassene], Souani, C.[Chokri], Besbes, K.[Kamel],
Real-time embedded system for traffic sign recognition based on ZedBoard,
RealTimeIP(16), No. 5, October 2019, pp. 1813-1823.
Springer DOI 1911
BibRef

Cui, Z.C.[Zhi-Chao], Liu, Y.H.[Yue-Hu], Ren, F.[Fuji],
Homography-based traffic sign localisation and pose estimation from image sequence,
IET-IPR(13), No. 14, 12 December 2019, pp. 2829-2839.
DOI Link 1912
BibRef

Ellahyani, A.[Ayoub], El Ansari, M.[Mohamed], Lahmyed, R.[Redouan], Tremeau, A.[Alain],
Traffic sign recognition method for intelligent vehicles,
JOSA-A(35), No. 11, November 2018, pp. 1907-1914.
DOI Link 1912
Feature extraction, Neural networks, Stochastic gradient descent, Stochastic processes, Visibility, Wavelets BibRef

Li, Y.[You], Wang, W.[Weixi], Li, X.M.[Xiao-Ming], Xie, L.F.[Lin-Fu], Wang, Y.K.[Yan-Kun], Guo, R.Z.[Ren-Zhong], Xiu, W.Q.[Wen-Qun], Tang, S.J.[Sheng-Jun],
Pole-Like Street Furniture Segmentation and Classification in Mobile LiDAR Data by Integrating Multiple Shape-Descriptor Constraints,
RS(11), No. 24, 2019, pp. xx-yy.
DOI Link 1912
BibRef

Tian, Y.[Yan], Gelernter, J.[Judith], Wang, X.[Xun], Li, J.Y.[Jian-Yuan], Yu, Y.Z.[Yi-Zhou],
Traffic Sign Detection Using a Multi-Scale Recurrent Attention Network,
ITS(20), No. 12, December 2019, pp. 4466-4475.
IEEE DOI 2001
Feature extraction, Convolution, Object detection, Task analysis, Image color analysis, Image edge detection, deep learning BibRef

Balado, J.[Jesús], González, E.[Elena], Arias, P.[Pedro], Castro, D.[David],
Novel Approach to Automatic Traffic Sign Inventory Based on Mobile Mapping System Data and Deep Learning,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link 2002
BibRef

Kamal, U., Tonmoy, T.I., Das, S., Hasan, M.K.,
Automatic Traffic Sign Detection and Recognition Using SegU-Net and a Modified Tversky Loss Function With L1-Constraint,
ITS(21), No. 4, April 2020, pp. 1467-1479.
IEEE DOI 2004
Image segmentation, Image color analysis, Task analysis, Training, Benchmark testing, Shape, Deep learning, Traffic sign detection, L1 constraint BibRef

Tabernik, D., Skocaj, D.,
Deep Learning for Large-Scale Traffic-Sign Detection and Recognition,
ITS(21), No. 4, April 2020, pp. 1427-1440.
IEEE DOI 2004
Deep learning, Benchmark testing, Task analysis, Proposals, Detectors, Manuals, Inventory management, Deep learning, traffic-sign inventory management BibRef

Hechri, A.[Ahmed], Mtibaa, A.[Abdellatif],
Two-stage traffic sign detection and recognition based on SVM and convolutional neural networks,
IET-IPR(14), No. 5, 17 April 2020, pp. 939-946.
DOI Link 2004
BibRef

He, Z.L.[Zhen-Li], Nan, F.T.[Feng-Tao], Li, X.F.[Xin-Fa], Lee, S.J.[Shin-Jye], Yang, Y.[Yun],
Traffic sign recognition by combining global and local features based on semi-supervised classification,
IET-ITS(14), No. 5, May 2020, pp. 323-330.
DOI Link 2005
BibRef

Zhou, S.C.[Shi-Chao], Deng, C.W.[Chen-Wei], Piao, Z.Q.[Zheng-Quan], Zhao, B.J.[Bao-Jun],
Few-shot traffic sign recognition with clustering inductive bias and random neural network,
PR(100), 2020, pp. 107160.
Elsevier DOI 2005
Traffic sign recognition, Few-shot learning, Clustering, Randomization, BibRef

Wang, H.F.[Hua-Feng], Yuan, R.S.[Ri-Sheng], Pan, H.X.[Hai-Xia], Liu, W.Q.[Wan-Quan], Xing, Z.Q.[Zhi-Qiang], Huang, J.[Jian],
Speed sign recognition in complex scenarios based on deep cascade networks,
IET-ITS(14), No. 6, June 2020, pp. 628-636.
DOI Link 2005
BibRef

Temel, D., Chen, M., AlRegib, G.,
Traffic Sign Detection Under Challenging Conditions: A Deeper Look into Performance Variations and Spectral Characteristics,
ITS(21), No. 9, September 2020, pp. 3663-3673.
IEEE DOI 2008
Video sequences, Lenses, Image color analysis, Detection algorithms, Cameras, machine learning BibRef

Gámez Serna, C., Ruichek, Y.[Yassine],
Traffic Signs Detection and Classification for European Urban Environments,
ITS(21), No. 10, October 2020, pp. 4388-4399.
IEEE DOI 2010
Image color analysis, Shape, Benchmark testing, Feature extraction, Task analysis, Roads, Europe, Convolutional neural networks, traffic signs in urban environments BibRef

Du, L.[Luyao], Ji, J.[Jun], Pei, Z.H.[Zhong-Hui], Zheng, H.J.[Hong-Jiang], Fu, S.Z.[Shuai-Zhi], Kong, H.Y.[Hai-Yang], Chen, W.[Wei],
Improved detection method for traffic signs in real scenes applied in intelligent and connected vehicles,
IET-ITS(14), No. 12, December 2020, pp. 1555-1564.
DOI Link 2011
BibRef

Liu, Z.W.[Zhan-Wen], Shen, C.[Chao], Fan, X.[Xing], Zeng, G.[Gaowen], Zhao, X.M.[Xiang-Mo],
Scale-aware limited deformable convolutional neural networks for traffic sign detection and classification,
IET-ITS(14), No. 12, December 2020, pp. 1712-1722.
DOI Link 2011
BibRef

Lei, Y.J.[Yin-Jie], Peng, D.[Duo], Zhang, P.P.[Ping-Ping], Ke, Q.U.[Qi-Uhong], Li, H.F.[Hai-Feng],
Hierarchical Paired Channel Fusion Network for Street Scene Change Detection,
IP(30), 2021, pp. 55-67.
IEEE DOI 2011
Feature extraction, Task analysis, Fuses, Semantics, Convolutional neural networks, Visualization, Surveillance, reverse spatial attention BibRef

Liu, H.[Hui], Lin, C.[Ciyun], Wu, D.[Dayong], Gong, B.[Bowen],
Slice-Based Instance and Semantic Segmentation for Low-Channel Roadside LiDAR Data,
RS(12), No. 22, 2020, pp. xx-yy.
DOI Link 2011
BibRef

Orellana, F.[Felipe], Blasco, J.M.D.[Jose Manuel Delgado], Foumelis, M.[Michael], d'Aranno, P.J.V.[Peppe J.V.], Marsella, M.A.[Maria A.], di Mascio, P.[Paola],
DInSAR for Road Infrastructure Monitoring: Case Study Highway Network of Rome Metropolitan (Italy),
RS(12), No. 22, 2020, pp. xx-yy.
DOI Link 2011
BibRef

Almutairy, F., Alshaabi, T., Nelson, J., Wshah, S.,
ARTS: Automotive Repository of Traffic Signs for the United States,
ITS(22), No. 1, January 2021, pp. 457-465.
IEEE DOI 2012
Europe, Roads, Automotive engineering, Object detection, Subspace constraints, Deep learning, Advanced driver-assistance, object detection BibRef

Tu, J., Yao, J., Li, L., Zhao, W., Xiang, B.,
Extraction of Street Pole-Like Objects Based on Plane Filtering From Mobile LiDAR Data,
GeoRS(59), No. 1, January 2021, pp. 749-768.
IEEE DOI 2012
Feature extraction, Data mining, Roads, Laser radar, Shape, Clustering algorithms, 3-D point cloud, pole-like objects BibRef

Yazdan, R., Varshosaz, M.,
Improving traffic sign recognition results in urban areas by overcoming the impact of scale and rotation,
PandRS(171), 2021, pp. 18-35.
Elsevier DOI 2012
Sign recognition, Perspective effects, Traffic signs BibRef

Huang, Y., Ma, P., Ji, Z., He, L.,
Part-Based Modeling of Pole-Like Objects Using Divergence-Incorporated 3-D Clustering of Mobile Laser Scanning Point Clouds,
GeoRS(59), No. 3, March 2021, pp. 2611-2626.
IEEE DOI 2103
Feature extraction, Shape, Urban areas, Solid modeling, Vegetation, Data mining, Adaptive growing, pole-like objects (PLOs) BibRef

Mao, Z.[Zhu], Zhang, F.[Fan], Huang, X.F.[Xian-Feng], Jia, X.Y.[Xiang-Yang], Gong, Y.P.[Yi-Ping], Zou, Q.[Qin],
Deep Neural Networks for Road Sign Detection and Embedded Modeling Using Oblique Aerial Images,
RS(13), No. 5, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Aslansefat, K.[Koorosh], Kabir, S.[Sohag], Abdullatif, A.[Amr], Vasudevan, V.[Vinod], Papadopoulos, Y.[Yiannis],
Toward Improving Confidence in Autonomous Vehicle Software: A Study on Traffic Sign Recognition Systems,
Computer(54), No. 8, August 2021, pp. 66-76.
IEEE DOI 2108
Software, Safety, Software measurement, Autonomous vehicles BibRef

Kong, G.[Gefei], Fan, H.C.[Hong-Chao],
Enhanced Facade Parsing for Street-Level Images Using Convolutional Neural Networks,
GeoRS(59), No. 12, December 2021, pp. 10519-10531.
IEEE DOI 2112
Grammar, Pipelines, Buildings, Image segmentation, Semantics, Shape, Object detection, Data set, deep learning, façade parsing, semantic segmentation BibRef

Cortés, A.[Andoni], Rodríguez, C.[Clemente], Vélez, G.[Gorka], Barandiarán, J.[Javier], Nieto, M.[Marcos],
Analysis of Classifier Training on Synthetic Data for Cross-Domain Datasets,
ITS(23), No. 1, January 2022, pp. 190-199.
IEEE DOI 2201
Training, Data models, Machine learning, Pipelines, Detectors, Vehicles, Synthetic datasets, deep learning, traffic sign recognition BibRef

Wang, Z.S.[Zheng-Shuai], Wang, J.Q.[Jian-Qiang], Li, Y.[Yali], Wang, S.J.[Sheng-Jin],
Traffic Sign Recognition With Lightweight Two-Stage Model in Complex Scenes,
ITS(23), No. 2, February 2022, pp. 1121-1131.
IEEE DOI 2202
Detectors, Task analysis, Feature extraction, Benchmark testing, Color, Interference, Indexes, Intelligent transportation system, refinement BibRef

Akallouch, M.[Mohammed], Boujemaa, K.S.[Kaoutar Sefrioui], Bouhoute, A.[Afaf], Fardousse, K.[Khalid], Berrada, I.[Ismail],
ASAYAR: A Dataset for Arabic-Latin Scene Text Localization in Highway Traffic Panels,
ITS(23), No. 4, April 2022, pp. 3026-3036.
IEEE DOI 2204
Artificial intelligence, Text recognition, Annotations, Roads, Vehicles, Meteorology, Scene text extraction, Arabic script, highway traffic signs BibRef

Vaidya, B.[Bhaumik], Paunwala, C.[Chirag],
Hardware Efficient Modified CNN Architecture for Traffic Sign Detection and Recognition,
IJIG(22), No. 2, April 2022, pp. 2250017.
DOI Link 2205
BibRef

Bravi, L.[Luca], Kubin, L.[Luca], Caprasecca, S.[Stefano], de Andrade, D.C.[Douglas Coimbra], Simoncini, M.[Matteo], Taccari, L.[Leonardo], Sambo, F.[Francesco],
Detection of Stop Sign Violations From Dashcam Data,
ITS(23), No. 6, June 2022, pp. 5411-5420.
IEEE DOI 2206
Videos, Feature extraction, Global Positioning System, Detectors, Pipelines, Vehicles, Benchmark testing, Stop sign violations, GPS BibRef

Ahmed, S.[Sabbir], Kamal, U.[Uday], Hasan, M.K.[Md. Kamrul],
DFR-TSD: A Deep Learning Based Framework for Robust Traffic Sign Detection Under Challenging Weather Conditions,
ITS(23), No. 6, June 2022, pp. 5150-5162.
IEEE DOI 2206
Training, Benchmark testing, Task analysis, Lenses, Image color analysis, Videos, Rain, Traffic sign detection, modular approach BibRef

Yang, B.S.[Bi-Sheng], Fang, L.[Lina], Li, J.[Jonathan],
Semi-Automated Extraction and Delineation of 3D Roads of Street Scene from Mobile Laser Scanning Point Clouds,
PandRS(79), No. 1, May 2013, pp. 80-93.
Elsevier DOI 1305
Mobile laser scanning; Curb detection; 3D road extraction; Scanning lines; Moving windows filtering
See also Semiautomated Extraction of Street Light Poles From Mobile LiDAR Point-Clouds. BibRef

Yang, B.S.[Bi-Sheng], Dong, Z.[Zhen], Liu, Y.[Yuan], Liang, F.[Fuxun], Wang, Y.J.[Yong-Jun],
Computing multiple aggregation levels and contextual features for road facilities recognition using mobile laser scanning data,
PandRS(126), No. 1, 2017, pp. 180-194.
Elsevier DOI 1704
BibRef
Earlier: Corrigendum: PandRS(151), 2019, pp. 14.
Elsevier DOI 1904
Point clouds processing BibRef

Zhou, Y.Z.[Yu-Zhou], Han, X.[Xu], Peng, M.J.[Ming-Jun], Li, H.T.[Hai-Ting], Yang, B.[Bo], Dong, Z.[Zhen], Yang, B.S.[Bi-Sheng],
Street-view imagery guided street furniture inventory from mobile laser scanning point clouds,
PandRS(189), 2022, pp. 63-77.
Elsevier DOI 2206
Street-view imagery, Mobile laser scanning, Point clouds, Street furniture, Instance segmentation, Neural network BibRef

Saito, Y.[Yuichi], Yoshimi, R.[Ryoma], Kume, S.[Shinichi], Shen, X.[Xun], Yamasaki, A.[Akito], Matsumi, R.[Ryosuke], Ito, T.[Takuma], Kinoshita, T.[Toshiki], Inoue, S.[Shintaro], Shimizu, T.[Tsukasa], Nagai, M.[Masao], Inoue, H.[Hideo], Raksincharoensak, P.[Pongsathorn],
Effectiveness of a Driver Assistance System With Deceleration Control and Brake Hold Functions in Stop Sign Intersection Scenarios,
ITS(23), No. 7, July 2022, pp. 8747-8758.
IEEE DOI 2207
Vehicles, Senior citizens, Brakes, Roads, Accidents, Task analysis, Hazards, Safety, potential hazard, driver assistance system, driver behavior BibRef

Yao, Y.B.[Ying-Biao], Han, L.[Li], Du, C.J.[Chen-Jie], Xu, X.[Xin], Jiang, X.[Xianyang],
Traffic sign detection algorithm based on improved YOLOv4-Tiny,
SP:IC(107), 2022, pp. 116783.
Elsevier DOI 2208
Traffic sign detection, YOLOv4-tiny, Small object, Adaptive feature pyramid network, Receptive field block BibRef

Kherraki, A.[Amine], Maqbool, M.[Muaz], El Ouazzani, R.[Rajae],
Robust Traffic Signs Classification using Deep Convolutional Neural Network,
ISCV22(1-6)
IEEE DOI 2208
Roads, Computational modeling, Neural networks, Feature extraction, Real-time systems, Belgium Traffic Sign Dataset. BibRef

Bagi, R.[Randheer], Dutta, T.[Tanima], Nigam, N.[Nitika], Verma, D.[Deepali], Gupta, H.P.[Hari Prabhat],
Met-MLTS: Leveraging Smartphones for End-to-End Spotting of Multilingual Oriented Scene Texts and Traffic Signs in Adverse Meteorological Conditions,
ITS(23), No. 8, August 2022, pp. 12801-12810.
IEEE DOI 2208
Text recognition, Image edge detection, Semantics, Feature extraction, Vehicles, Convolution, Roads, Text spotting, noisy images BibRef

Yu, J.[Jing], Ye, X.J.[Xiao-Jun], Tu, Q.[Qiang],
Traffic Sign Detection and Recognition in Multiimages Using a Fusion Model With YOLO and VGG Network,
ITS(23), No. 9, September 2022, pp. 16632-16642.
IEEE DOI 2209
Image recognition, Feature extraction, Image color analysis, Shape, Deep learning, Support vector machines, Roads, VGG19 BibRef

Min, W.D.[Wei-Dong], Liu, R.K.[Rui-Kang], He, D.J.[Dao-Jing], Han, Q.[Qing], Wei, Q.T.[Qing-Ting], Wang, Q.[Qi],
Traffic Sign Recognition Based on Semantic Scene Understanding and Structural Traffic Sign Location,
ITS(23), No. 9, September 2022, pp. 15794-15807.
IEEE DOI 2209
Feature extraction, Semantics, Image color analysis, Shape, Roads, Image segmentation, Task analysis, Traffic sign recognition, structural traffic sign location BibRef

Chen, W.Z.[Wen-Zhe], Childs, J.[Joshua], Ray, S.[Saraf], Lee, B.S.[Byung Suk], Xia, T.[Tian],
RFID Technology Study for Traffic Signage Inventory Management Application,
ITS(23), No. 10, October 2022, pp. 17809-17818.
IEEE DOI 2210
Antennas, RFID tags, Databases, Inventory management, Transportation, Roads, Real-time systems, Radio-frequency identification (RFID), handheld RFID reader BibRef

Sharma, V.[Vipul], Dhiman, P.[Pankaj], Rout, R.K.[Ranjeet Kumar],
Improved traffic sign recognition algorithm based on YOLOv4-tiny,
JVCIR(91), 2023, pp. 103774.
Elsevier DOI 2303
Traffic sign, YOLO, Attention networks, Octave convolutions, Computer vision BibRef

Batool, A.[Aisha], Nisar, M.W.[Muhammad Wasif], Khan, M.A.[Muhammad Attique], Shah, J.H.[Jamal Hussain], Tariq, U.[Usman], Damaševicius, R.[Robertas],
Traffic sign recognition using proposed lightweight twig-net with linear discriminant classifier for biometric application,
IVC(135), 2023, pp. 104711.
Elsevier DOI 2306
Traffic sign, Classification, Machine learning, Autonomous vehicles, Computer vision BibRef

Xu, J.[Jian], Huang, Y.C.[Yu-Chun], Ying, D.[Dakan],
Traffic Sign Detection and Recognition Using Multi-Frame Embedding of Video-Log Images,
RS(15), No. 12, 2023, pp. xx-yy.
DOI Link 2307
BibRef

Mishra, A.[Ashutosh], Kumar, A.[Aman], Mandloi, S.[Shubham], Anand, K.[Khushboo], Zakkam, J.[John], Sowmya, S.[Seeram], Thakur, A.[Avinash],
Evaluating and Bench-marking Object Detection Models for Traffic Sign and Traffic Light Datasets,
ACCVWS22(345-359).
Springer DOI 2307
BibRef

Wang, Y.[Yue], Liu, M.J.[Min-Jie], Ren, Y.L.[Yan-Li], Zhang, X.P.[Xin-Peng], Feng, G.R.[Guo-Rui],
Traffic sign attack via pinpoint region probability estimation network,
PR(146), 2024, pp. 110035.
Elsevier DOI 2311
Adversarial examples, Traffic sign attack, AI security, Neural networks, Probability estimation BibRef

Gray, N.[Nicholas], Moraes, M.[Megan], Bian, J.[Jiang], Wang, A.[Alex], Tian, A.[Allen], Wilson, K.[Kurt], Huang, Y.[Yan], Xiong, H.[Haoyi], Guo, Z.[Zhishan],
GLARE: A Dataset for Traffic Sign Detection in Sun Glare,
ITS(24), No. 11, November 2023, pp. 12323-12330.
IEEE DOI Code:
WWW Link. 2311
BibRef

Cao, W.P.[Wei-Peng], Wu, Y.H.[Yu-Hao], Chakraborty, C.[Chinmay], Li, D.[Dachuan], Zhao, L.[Liang], Ghosh, S.K.[Soumya Kanti],
Sustainable and Transferable Traffic Sign Recognition for Intelligent Transportation Systems,
ITS(24), No. 12, December 2023, pp. 15784-15794.
IEEE DOI 2312
BibRef

Wang, J.F.[Jun-Fan], Chen, Y.[Yi], Ji, X.Y.[Xiao-Yue], Dong, Z.K.[Zhe-Kang], Gao, M.Y.[Ming-Yu], Lai, C.S.[Chun Sing],
Vehicle-Mounted Adaptive Traffic Sign Detector for Small-Sized Signs in Multiple Working Conditions,
ITS(25), No. 1, January 2024, pp. 710-724.
IEEE DOI 2402
Feature extraction, Detectors, Optimization, Object detection, Adaptive systems, Image color analysis, Filtering, traffic sign detection BibRef

Guo, Y.F.[Yun-Fei], Feng, W.[Wei], Yin, F.[Fei], Liu, C.L.[Cheng-Lin],
SignParser: An End-to-End Framework for Traffic Sign Understanding,
IJCV(132), No. 3, March 2024, pp. 805-821.
Springer DOI 2402
BibRef

Li, Y.Q.[Yong-Qiang], Wu, J.[Jiale], Liu, H.Y.[Hui-Yun], Ren, J.Z.[Jing-Zhi], Xu, Z.H.[Zhi-Hua], Zhang, J.[Jian], Wang, Z.Y.[Zhi-Yao],
Classification of Typical Static Objects in Road Scenes Based on LO-Net,
RS(16), No. 4, 2024, pp. 663.
DOI Link 2402
BibRef

Qian, Y.J.[Yue Jing], Wang, B.[Bo],
TSDet: A new method for traffic sign detection based on YOLOv5-SwinT,
IET-IPR(18), No. 4, 2024, pp. 875-885.
DOI Link 2403
computer vision, image recognition, object detection BibRef

He, L.W.[Le-Wei], Lan, F.[Fucai], Zhou, C.Z.[Chuan-Zhe], Ye, Y.G.[Yao-Guang], Zhang, W.C.[Wen-Cong], Chen, B.Z.[Bing-Zhi], Pan, J.[Jiahui],
A feature-enhanced hybrid attention network for traffic sign recognition in real scenes,
IET-IPR(18), No. 8, 2024, pp. 2064-2077.
DOI Link 2406
deep learning, object detection, traffic sign recognition BibRef

Li, Z.[Zhishan], Chen, H.X.[Hong-Xu], Biggio, B.[Battista], He, Y.F.[Yi-Fan], Cai, H.R.[Hao-Ran], Roli, F.[Fabio], Xie, L.[Lei],
Toward Effective Traffic Sign Detection via Two-Stage Fusion Neural Networks,
ITS(25), No. 8, August 2024, pp. 8283-8294.
IEEE DOI 2408
Detectors, YOLO, Image resolution, Optimization, Convolutional neural networks, Real-time systems, Fuses, lightweight BibRef

Wang, Z.Q.[Zi-Qi], Wang, X.F.[Xiao-Fei], Li, J.[Jun], Yao, J.B.[Jiang-Bei],
Evaluation of Traffic Sign Occlusion Rate Based on a 3D Point Cloud Space,
RS(16), No. 16, 2024, pp. 2872.
DOI Link 2408
BibRef

Du, S.J.[Song-Jie], Pan, W.G.[Wei-Guo], Li, N.[Nuoya], Dai, S.Y.[Song-Yin], Xu, B.X.[Bing-Xin], Liu, H.Z.[Hong-Zhe], Xu, C.[Cheng], Li, X.[Xuewei],
TSD-YOLO: Small traffic sign detection based on improved YOLO v8,
IET-IPR(18), No. 11, 2024, pp. 2884-2898.
DOI Link Code:
WWW Link. 2409
computer vision, convolutional neural nets, object detection BibRef

Uikey, R.[Rishabh], Lone, H.R.[Haroon R.], Agarwal, A.[Akshay],
Indian Traffic Sign Detection and Classification Through a Unified Framework,
ITS(25), No. 10, October 2024, pp. 14866-14875.
IEEE DOI 2410
Cameras, Image color analysis, Feature extraction, Classification algorithms, Videos, Vehicles, Shape, traffic sign classification BibRef

Sarwatt, D.S.[Doreen Sebastian], Kulwa, F.[Frank], Ding, J.G.[Jian-Guo], Ning, H.S.[Huan-Sheng],
Adapting Image Classification Adversarial Detection Methods for Traffic Sign Classification in Autonomous Vehicles: A Comparative Study,
ITS(25), No. 11, November 2024, pp. 19046-19061.
IEEE DOI 2411
Perturbation methods, Safety, Autonomous vehicles, Real-time systems, Image classification, Complexity theory, traffic sign classification BibRef

Yang, C.[Chuang], Zhuang, K.[Kai], Chen, M.[Mulin], Ma, H.Z.[Hao-Zhao], Han, X.[Xu], Han, T.[Tao], Guo, C.X.[Chang-Xing], Han, H.[Han], Zhao, B.X.[Bing-Xuan], Wang, Q.[Qi],
Traffic Sign Interpretation via Natural Language Description,
ITS(25), No. 11, November 2024, pp. 18939-18953.
IEEE DOI 2411
Symbols, Task analysis, Semantics, Assistive technologies, Natural languages, Logic, Text recognition, Traffic sign detection, intelligent transportation BibRef

Wang, T.T.[Ting-Ting], Hu, Y.F.[Yun-Feng], Fang, Q.[Qiang], He, B.[Banben], Gong, X.[Xun], Wang, P.[Ping],
DK-Former: A Hybrid Structure of Deep Kernel Gaussian Process Transformer Network for Enhanced Traffic Sign Recognition,
ITS(25), No. 11, November 2024, pp. 18561-18572.
IEEE DOI Code:
WWW Link. 2411
Kernel, Transformers, Feature extraction, Convolution, Computational modeling, Autonomous vehicles, Accuracy, traffic sign recognition BibRef

An, F.[Fengping], Wang, J.R.[Jiang-Rong], Liu, R.[Ruijun],
Road Traffic Sign Recognition Algorithm Based on Cascade Attention-Modulation Fusion Mechanism,
ITS(25), No. 11, November 2024, pp. 17841-17851.
IEEE DOI 2411
Feature extraction, Computational modeling, Accuracy, Deep learning, Target recognition, Road traffic, feature enhancement BibRef

Shi, J.Y.[Jing-Yi], Rao, H.[Huanle], Jing, Q.[Qinyang], Wen, Z.Q.[Zi-Qiang], Jia, G.[Gangyong],
FlexibleCP: A data augmentation strategy for traffic sign detection,
IET-IPR(18), No. 12, 2024, pp. 3667-3680.
DOI Link 2411
intelligent transportation systems, object detection BibRef

Peng, F.[Fei], Zhang, Z.[Zhe], Ding, Q.Y.[Qing-Yan],
Analysis of Guidance Signage Systems from a Complex Network Theory Perspective: A Case Study in Subway Stations,
IJGI(13), No. 10, 2024, pp. 342.
DOI Link 2411
BibRef

Wang, R.[Runmin], Zhu, Y.[Yanbin], Chen, H.[Hua], Zhu, Z.[Zhenlin], Zhang, X.Y.[Xiang-Yu], Ding, Y.J.[Ya-Jun], Qian, S.[Shengyou], Gao, C.X.[Chang-Xin], Liu, L.[Li], Sang, N.[Nong],
TTDNet: An End-to-End Traffic Text Detection Framework for Open Driving Environments,
ITS(25), No. 12, December 2024, pp. 19770-19784.
IEEE DOI Code:
WWW Link. 2412
Text detection, Accuracy, Feature extraction, Shape, Image segmentation, Intelligent transportation systems, feature enhancement BibRef

Wang, Y.J.[Yig-Jie], Huang, W.G.[Wei-Guo], Li, J.J.[Jia-Jie], Du, G.F.[Gui-Fu], Wang, X.[Xiang], Wen-Juan, E., Shi, J.J.[Juan-Juan],
A More Balanced Loss-Reweighting Method for Long-Tailed Traffic Sign Detection and Recognition,
ITS(25), No. 12, December 2024, pp. 20729-20740.
IEEE DOI 2412
Training, Tail, Accuracy, Adaptation models, Roads, Meteorology, Intelligent transportation systems, loss reweighting BibRef

Abdi, N.[Nariman], Parvaresh, F.[Farzad], Sabahi, M.F.[Mohamad Farzan],
SeqNet: Sequential Networks for One-Shot Traffic Sign Recognition With Transfer Learning,
ITS(25), No. 12, December 2024, pp. 20435-20445.
IEEE DOI 2412
Feature extraction, Training, One shot learning, Image recognition, Transfer learning, Few shot learning, Symbols, One-shot learning, logo identification BibRef

Li, Y.Q.[Yu-Qi], Wang, Z.J.[Zi-Jian], Zhang, H.[Han], Yao, X.P.[Xin-Peng], Zhou, Z.[Zhou], Cheng, X.[Xin],
A small-target traffic sign detection algorithm based on partial conv and atrous spatial pyramid,
IET-IPR(18), No. 14, 2024, pp. 4639-4652.
DOI Link 2501
object detection, object recognition, road traffic, small target detection BibRef

Kherraki, A.[Amine], El Ouazzani, R.[Rajae],
A Survey on Traffic Sign Classification using Artificial Intelligence Techniques,
ISCV24(1-6)
IEEE DOI 2408
Surveys, Measurement, Technological innovation, Roads, Transportation, Lighting, Intelligent Transportation Systems, Traffic Sign Classification BibRef

Hsiao, T.F.[Teng-Fang], Huang, B.L.[Bo-Lun], Ni, Z.X.[Zi-Xiang], Lin, Y.T.[Yan-Ting], Shuai, H.H.[Hong-Han], Li, Y.H.[Yung-Hui], Cheng, W.H.[Wen-Huang],
Natural Light Can Also be Dangerous: Traffic Sign Misinterpretation Under Adversarial Natural Light Attacks,
WACV24(3903-3912)
IEEE DOI 2404
Training, Machine learning algorithms, Machine learning, Robustness, Object recognition, Task analysis, Algorithms, Image recognition and understanding BibRef

Sharma, V.[Vinayak], Kumar, V.[Vimal], Aditya, H.[Harshvardhan],
Traffic Sign Detection and Classification,
ICCVMI23(1-6)
IEEE DOI 2403
Technological innovation, System performance, Computer architecture, Prediction algorithms, Road safety, CNN BibRef

Shi, W.J.[Wen-Jun], Shi, Y.J.[Ying-Jun], Zhu, D.C.[Dong-Chen], Zhang, X.L.[Xiao-Lin], Li, J.[Jiamao],
Traffic Sign Instances Segmentation Using Aliased Residual Structure and Adaptive Focus Localizer,
ICPR22(3676-3685)
IEEE DOI 2212
Location awareness, Adaptation models, Image recognition, Text recognition, Optical character recognition, Prototypes, Assistive technologies BibRef

Le, H.[Huy], Nguyen, M.[Minh], Yan, W.Q.[Wei Qi], Lo, S.[Saide],
Training a convolutional neural network for transportation sign detection using synthetic dataset,
IVCNZ21(1-6)
IEEE DOI 2201
Training, Annotations, Computational modeling, Neural networks, Transportation, Graphics processing units, Training data, Synthetic dataset generation BibRef

Sanjeewani, P.[Pubudu], Verma, B.[Brijesh], Affum, J.[Joseph],
Multi-stage Deep Learning Technique for Improving Traffic Sign Recognition,
IVCNZ21(1-6)
IEEE DOI 2201
Deep learning, Image recognition, Text recognition, Shape, Image color analysis, Optical imaging, Character recognition, optical character recognition BibRef

Wang, C.L.[Cheng-Liang], Xie, X.[Xin], Liao, C.[Chao],
An Adaptive Fusion Model Based on Kalman Filtering and LSTM for Fast Tracking of Road Signs,
ICPR21(1414-1421)
IEEE DOI 2105
Location awareness, Adaptation models, Image color analysis, Roads, Detectors, Predictive models, ThunderNet, road-sign detection and tracking BibRef

Wang, Z.H.[Zhe-Hui], Zhao, S.Y.[San-Yuan], Shen, J.B.[Jian-Bing], Lei, Z.C.[Zheng-Chao],
Efficient Light Deep Network for Street Scene Parsing,
VCIP20(42-45)
IEEE DOI 2102
feature extraction, image segmentation, learning (artificial intelligence), object detection, real-time BibRef

Wei, Z., Gu, H., Zhang, W.,
The Relation between the Arrangements of the Information on the Sign and the Cognitive Levels of the Sign,
CVIDL20(431-441)
IEEE DOI 2102
cognitive systems, road safety, road traffic, traffic engineering computing, information orientations, destination BibRef

Ertler, C.[Christian], Mislej, J.[Jerneja], Ollmann, T.[Tobias], Porzi, L.[Lorenzo], Neuhold, G.[Gerhard], Kuang, Y.B.[Yu-Bin],
The Mapillary Traffic Sign Dataset for Detection and Classification on a Global Scale,
ECCV20(XXIII:68-84).
Springer DOI 2011
BibRef

Ao, Y., Wang, J., Zhou, M., Lindenbergh, R.C., Yang, M.Y.,
Fully Convolutional Networks for Street Furniture Identification In Panorama Images,
Semantics3D19(13-20).
DOI Link 1912
BibRef

Singh, P.[Pravendra], Manikandan, R., Matiyali, N.[Neeraj], Namboodiri, V.[Vinay],
Multi-Layer Pruning Framework for Compressing Single Shot MultiBox Detector,
WACV19(1318-1327)
IEEE DOI 1904
Apply to traffic signs. data compression, feature extraction, image classification, image recognition, learning (artificial intelligence), Training BibRef

Wang, W.Z.[Wen-Zhe], Wu, B.[Bin], Lv, J.[Jinna], Dai, P.[Pilin],
Regular and Small Target Detection,
MMMod19(II:453-464).
Springer DOI 1901
Traffic signs. BibRef

Pon, A.D., Adrienko, O., Harakeh, A., Waslander, S.L.,
A Hierarchical Deep Architecture and Mini-batch Selection Method for Joint Traffic Sign and Light Detection,
CRV18(102-109)
IEEE DOI 1812
Proposals, Graphics processing units, Object detection, Detectors, Image color analysis, object detection, autonomous driving, traffic light BibRef

Luo, H., Kong, Q., Wu, F.,
Traffic Sign Image Synthesis with Generative Adversarial Networks,
ICPR18(2540-2545)
IEEE DOI 1812
Standards, Lighting, Training, Visualization, Image generation, Generative adversarial networks BibRef

Uittenbogaard, R., Sebastian, C., Viiverberg, J., Boom, B.J., de With, P.H.N.,
Conditional Transfer with Dense Residual Attention: Synthesizing traffic signs from street-view imagery,
ICPR18(553-559)
IEEE DOI 1812
Generators, Decoding, Training, Convolution, Generative adversarial networks, Iron BibRef

Frejlichowski, D.[Dariusz], Mikolajczak, P.[Piotr],
A System for Automatic Town Sign Recognition for Driver Assistance Systems,
ICCVG18(115-124).
Springer DOI 1810
BibRef

El Ouadrhiri, A.A.[Abderrahmane Adoui], Burian, J.[Jaroslav], Andaloussi, S.J.[Said Jai], El Morabet, R.[Rachida], Ouchetto, O.[Ouail], Sekkaki, A.[Abderrahim],
Fast-Tracking Application for Traffic Signs Recognition,
ICCVG18(385-396).
Springer DOI 1810
BibRef

Palummo, A.,
From The Road Sign To The Map: 3d Modeling In Support Of The Urban And Rural Road Conditions,
GeomCultural17(77-80).
DOI Link 1805
BibRef

Cheng, P.[Peng], Liu, W.[Wu], Zhang, Y.F.[Yi-Fan], Ma, H.D.[Hua-Dong],
LOCO: Local Context Based Faster R-CNN for Small Traffic Sign Detection,
MMMod18(I:329-341).
Springer DOI 1802
BibRef

Huang, H., Hou, L.Y.,
Speed Limit Sign Detection Based on Gaussian Color Model and Template Matching,
ICVISP17(118-122)
IEEE DOI 1712
Signal processing, Gaussian color model, Image segmentation, Thresholding segmentation, Traffic sign detection BibRef

Song, J.R.[Jia-Rong], Yang, Z.[Zhong], Zhang, T.Y.[Tian-Yi], Han, J.[Jia_Ming],
Design and Optimization of the Model for Traffic Signs Classification Based on Convolutional Neural Networks,
CVS17(394-403).
Springer DOI 1711
BibRef

Bouti, A., Mahraz, M.A., Riffi, J., Tairi, H.,
Road sign recognition with Convolutional Neural Network,
ISCV18(1-7)
IEEE DOI 1807
BibRef
Earlier:
Robust system for road sign detection and recognition using template matching,
ISCV17(1-4)
IEEE DOI 1710
feature extraction, image classification, neural nets, object recognition, road traffic, traffic engineering computing, Road Sign Recognition. Image color analysis, Lighting, Shape, Template Matching. BibRef

Zhang, F.[Fan], Ji, R.R.[Rui-Rui], Jiao, S.B.[Shang-Bin], Qi, K.J.[Kai-Jie],
A novel saliency computation model for traffic sign detection,
ICIVC17(31-35)
IEEE DOI 1708
Clustering algorithms, Computational modeling, Feature extraction, Image color analysis, Image edge detection, Neural networks, Visualization, clustering, saliency map, self-organizing map neural network, traffic, sign, detection BibRef

Ardianto, S., Chen, C.J., Hang, H.M.,
Real-time traffic sign recognition using color segmentation and SVM,
WSSIP17(1-5)
IEEE DOI 1707
Gabor filters, Histograms, Image color analysis, Image segmentation, Real-time systems, Support vector machines, Binary SVM, Color Segmentation, Gabor filter, HOG, Traffic, Sign, Recognition BibRef

Hienonen, P.[Petri], Lensu, L.[Lasse], Melander, M.[Markus], Kälviäinen, H.[Heikki],
Towards Condition Analysis for Machine Vision Based Traffic Sign Inventory,
ACIVS17(212-224).
Springer DOI 1712
BibRef
Earlier:
Framework for Machine Vision Based Traffic Sign Inventory,
SCIA17(I: 197-208).
Springer DOI 1706
BibRef

Xiao, Z., Yang, Z., Geng, L., Zhang, F.,
Traffic Sign Detection Based on Histograms of Oriented Gradients and Boolean Convolutional Neural Networks,
CMVIT17(111-115)
IEEE DOI 1704
Boolean functions BibRef

Zhu, Z., Liang, D., Zhang, S., Huang, X., Li, B., Hu, S.,
Traffic-Sign Detection and Classification in the Wild,
CVPR16(2110-2118)
IEEE DOI 1612
BibRef

Youssef, A.[Ali], Albani, D.[Dario], Nardi, D.[Daniele], Bloisi, D.D.[Domenico Daniele],
Fast Traffic Sign Recognition Using Color Segmentation and Deep Convolutional Networks,
ACIVS16(205-216).
Springer DOI 1611
BibRef

Wiesemann, T.[Thomas], Jiang, X.Y.[Xiao-Yi],
Fog Augmentation of Road Images for Performance Analysis of Traffic Sign Detection Algorithms,
ACIVS16(685-697).
Springer DOI 1611
BibRef

Li, Y.H., Shinohara, T., Satoh, T., Tachibana, K.,
Road Signs Detection And Recognition Utilizing Images And 3d Point Cloud Acquired By Mobile Mapping System,
ISPRS16(B1: 669-673).
DOI Link 1610
BibRef

Soilán, M., Riveiro, B., Martínez-Sánchez, J., Arias, P.,
Automatic Road Sign Inventory Using Mobile Mapping Systems,
ISPRS16(B3: 717-723).
DOI Link 1610
BibRef

Yao, Q., Tan, B., Huang, Y.,
Fast Drawing Of Traffic Sign Using Mobile Mapping System,
ISPRS16(B3: 937-944).
DOI Link 1610
BibRef

Li, Y., Fan, J., Huang, Y., Chen, Z.,
Lidar-incorporated Traffic Sign Detection From Video Log Images Of Mobile Mapping System,
ISPRS16(B1: 661-668).
DOI Link 1610
BibRef

Tsai, V.J.D.[Victor J. D.], Chen, J.H.[Jyun-Han], Huang, H.S.[Hsun-Sheng],
Traffic Sign Inventory From Google Street View Images,
ISPRS16(B4: 243-246).
DOI Link 1610
BibRef

Tastimur, C., Karaköse, M., Çelik, Y., Akin, E.,
Image processing based traffic sign detection and recognition with fuzzy integral,
WSSIP16(1-4)
IEEE DOI 1608
fuzzy set theory BibRef

Agudo, D., Sánchez, Á., Vélez, J.F., Belén Moreno, A.,
Real-time railway speed limit sign recognition from video sequences,
WSSIP16(1-4)
IEEE DOI 1608
image sequences BibRef

Ben Romdhane, N.[Nadra], Mliki, H.[Hazar], El Beji, R.[Rabii], Hammami, M.[Mohamed],
A Comparative Study of Vision-Based Traffic Signs Recognition Methods,
ICIAR16(341-348).
Springer DOI 1608

See also Comparative Study of Vision-Based Lane Detection Methods, A. BibRef

Gim, J.[JaWon], Hwang, M.[MinCheol], Ko, B.C.[Byoung Chul], Nam, J.Y.[Jae-Yeal],
Real-Time Speed-Limit Sign Detection and Recognition Using Spatial Pyramid Feature and Boosted Random Forest,
ICIAR15(437-445).
Springer DOI 1507
BibRef

Frejlichowski, D.[Dariusz],
Application of the Polar: Fourier Greyscale Descriptor to the Automatic Traffic Sign Recognition,
ICIAR15(506-513).
Springer DOI 1507
BibRef

Belaroussi, R.[Rachid], Gruyer, D.[Dominique],
Road sign-aided estimation of visibility conditions,
MVA15(202-205)
IEEE DOI 1507
Cameras; Detectors; Estimation; Radar; Roads; Vehicles; Visualization BibRef

Pritt, C.,
Road sign detection on a smartphone for traffic safety,
AIPR14(1-6)
IEEE DOI 1504
computer vision BibRef

Hazelhoff, L.[Lykele], Creusen, I.M.[Ivo M.], de With, P.H.N.[Peter H.N.],
Optimal Performance-Efficiency Trade-off for Bag of Words Classification of Road Signs,
ICPR14(2996-3001)
IEEE DOI 1412
Dictionaries BibRef

Varela-González, M., Riveiro, B., Arias-Sánchez, P., González-Jorge, H., Martínez-Sánchez, J.,
A CityGML extension for traffic-sign objects that guides the automatic processing of data collected using Mobile Mapping technology,
LandImaging14(415-420).
DOI Link 1411
BibRef

Fernandes, K.[Kelwin], Silva, P.F.B.[Pedro F. B.], Ciobanu, L.[Lucian], Fonseca, P.[Paulo],
Catalogue-Based Traffic Sign Asset Management: Towards User's Effort Minimisation,
ICIAR14(I: 301-308).
Springer DOI 1410
BibRef

Tang, S.S.[Sui-Sui], Huang, L.L.[Lin-Lin],
Traffic Sign Recognition Using Complementary Features,
ACPR13(210-214)
IEEE DOI 1408
feature extraction BibRef

Zhu, Y.Y.[Ying-Ying], Wang, X.G.[Xing-Gang], Yao, C.[Cong], Bai, X.[Xiang],
Traffic sign classification using two-layer image representation,
ICIP13(3755-3759)
IEEE DOI 1402
Locality-constrained Linear Coding BibRef

Parra, A.[Albert], Zhao, B.[Bin], Haddad, A.[Andrew], Boutin, M.[Mireille], Delp, E.J.[Edward J.],
Hazardous material sign detection and recognition,
ICIP13(2640-2644)
IEEE DOI 1402
Hough Transform; Sign detection; saliency map; shape detection BibRef

Zhang, T.[Tao], Lv, J.Q.[Jing-Qin], Yang, J.[Jie],
Road sign detection based on visual saliency and shape analysis,
ICIP13(3667-3670)
IEEE DOI 1402
Improved radial symmetry transform (IRST) BibRef

Moiseev, B.[Boris], Konev, A.[Artem], Chigorin, A.[Alexander], Konushin, A.[Anton],
Evaluation of Traffic Sign Recognition Methods Trained on Synthetically Generated Data,
ACIVS13(576-583).
Springer DOI 1311
BibRef

Choi, C.W.[Chang-Won], Choi, S.I.[Sung-In], Park, S.Y.[Soon-Yong],
Efficient Detection and Tracking of Road Signs Based on Vehicle Motion and Stereo Vision,
ACIVS13(608-619).
Springer DOI 1311
BibRef

Ellis, L., Pugeault, N., Ofjall, K., Hedborg, J., Bowden, R., Felsberg, M.,
Autonomous navigation and sign detector learning,
WORV13(144-151)
IEEE DOI 1307
control engineering computing BibRef

Miyata, S.[Shigeharu], Takehara, S.[Shin], Sakai, H.[Hideki], Ishikawa, T.[Takahiro],
Method for recognition of numbers on speed limit signs utilizing an eigen space method based on the KL transform,
ICARCV12(377-382).
IEEE DOI 1304
BibRef

Liu, W.[Wei], Wu, Y.H.[Yong-Hua], Lv, J.[Jin], Yuan, H.[Huai], Zhao, H.[Hong],
U.S. speed limit sign detection and recognition from image sequences,
ICARCV12(1437-1442).
IEEE DOI 1304
BibRef

Li, C.[Ce], Hu, Y.L.[Ya-Ling], Xiao, L.[Limei], Tian, L.H.[Li-Hua],
Salient traffic sign recognition based on sparse representation of visual perception,
CVRS12(273-278).
IEEE DOI 1302
BibRef

Hu, X., Zhu, X., Li, D.,
Traffic Sign Detection Based On Biologically Visual Mechanism,
ISPRS12(XXXIX-B3:217-221).
DOI Link 1209
BibRef

Shahbazi, M., Sattari, M., Homayouni, S., Saadatseresht, M.,
Implementation And Evaluation Of A Mobile Mapping System Based On Integrated Range And Intensity Images For Traffic Signs Localization,
ISPRS12(XXXIX-B5:51-56).
DOI Link 1209
BibRef
And: ISPRS12(XXXIX-B5:505-510).
DOI Link 1209
BibRef

Vavilin, A., Deb, K., Kim, T.H., Jo, K.,
Road sign detection method based on fast HDR image generation technique,
IVCNZ10(1-8).
IEEE DOI 1203
BibRef

Hazelhoff, L.[Lykele], Creusen, I.M.[Ivo M.], de With, P.H.N.[Peter H.N.],
Robust classification system with reliability prediction for semi-automatic traffic-sign inventory systems,
WACV13(125-132).
IEEE DOI 1303
BibRef
Earlier:
Robust classification of traffic signs using multi-view cues,
ICIP12(457-460).
IEEE DOI 1302
BibRef
And:
Robust detection, classification and positioning of traffic signs from street-level panoramic images for inventory purposes,
WACV12(313-320).
IEEE DOI 1203
BibRef

Creusen, I.M.[Ivo M.], Hazelhoff, L.[Lykele], de With, P.H.N.[Peter H.N.],
Color transformation for improved traffic sign detection,
ICIP12(461-464).
IEEE DOI 1302
BibRef

Creusen, I.M., Wijnhoven, R.G.J., Herbschleb, E., de With, P.H.N.,
Color exploitation in hog-based traffic sign detection,
ICIP10(2669-2672).
IEEE DOI 1009
BibRef

Deguchi, D.[Daisuke], Doman, K.[Keisuke], Ide, I.[Ichiro], Murase, H.[Hiroshi],
Improvement of a Traffic Sign Detector by Retrospective Gathering of Training Samples from In-Vehicle Camera Image Sequences,
CVVT10(204-213).
Springer DOI 1109
BibRef

Chen, Z.X.[Zhi-Xie], Yang, J.[Jing], Kong, B.[Bin],
A Robust Traffic Sign Recognition System for Intelligent Vehicles,
ICIG11(975-980).
IEEE DOI 1109
BibRef

Ihara, A.[Arihito], Fujiyoshi, H.[Hironobu], Takagi, M.[Masanari], Kumon, H.[Hiroaki], Tamatsu, Y.[Yukimasa],
Improved Matching Accuracy in Traffic Sign Recognition by Using Different Feature Subspaces,
MVA09(130-).
PDF File. 0905
BibRef

Ninot, J.[Jérôme], Smadja, L.[Laurent], Heggarty, K.[Kevin],
Road Sign Recognition Using A Hybrid Evolutionary Algorithm And Primitives Fusion,
PCVIA10(A:287).
PDF File. 1009
BibRef

Belaroussi, R.[Rachid], Foucher, P.[Philippe], Tarel, J.P.[Jean-Philippe], Soheilian, B.[Bahman], Charbonnier, P.[Pierre], Paparoditis, N.[Nicolas],
Road Sign Detection in Images: A Case Study,
ICPR10(484-488).
IEEE DOI 1008
BibRef

Li, Y.[Ying], Pankanti, S.[Sharath], Guan, W.G.[Wei-Guang],
Real-Time Traffic Sign Detection: An Evaluation Study,
ICPR10(3033-3036).
IEEE DOI 1008
BibRef

Muyan-Özçelik, P.[Pinar], Glavtchev, V.[Vladimir], Ota, J.M.[Jeffrey M.], Owens, J.D.[John D.],
A Template-Based Approach for Real-Time Speed-Limit-Sign Recognition on an Embedded System Using GPU Computing,
DAGM10(162-171).
Springer DOI 1009
BibRef

Chen, C.[Cheng], Tian, Y.[Yingli],
Door detection via signage context-based Hierarchical Compositional Model,
UCVP10(1-6).
IEEE DOI 1006
Not roads, but signs. BibRef

Xu, Q.S.[Qing-Song], Su, J.[Juan], Liu, T.T.[Tian-Tian],
A detection and recognition method for prohibition traffic signs,
IASP10(583-586).
IEEE DOI 1004
BibRef

Li, Q.[Qi], Tao, D.C.[Da-Cheng],
Detecting image points of general imbalance,
ICIP09(337-340).
IEEE DOI 0911
for road signs. In sparse textures. BibRef

Khan, J.F.[Jesmin F.], Bhuiyan, S.M.A.[Sharif M. A.], Adhami, R.R.[Reza R.],
Distortion invariant road sign detection,
ICIP09(841-844).
IEEE DOI 0911
BibRef

Fifik, M., Turan, J., Ovsenik, L.,
Detection System for Traffic Road Signs in Surrounding Environment,
WSSIP09(1-4).
IEEE DOI 0906
BibRef

Ren, F.X.[Fei-Xiang], Huang, J.S.[Jin-Sheng], Jiang, R.[Ruyi], Klette, R.,
General traffic sign recognition by feature matching,
IVCNZ09(409-414).
IEEE DOI 0911
BibRef

Belaroussi, R.[Rachid], Tarel, J.P.[Jean-Philippe],
Angle vertex and bisector geometric model for triangular road sign detection,
WACV09(1-7).
IEEE DOI 0912
BibRef
And:
A Real-Time Road Sign Detection Using Bilateral Chinese Transform,
ISVC09(II: 1161-1170).
Springer DOI 0911

See also Real Time Fingers Detection by Symmetry Transform Using a Two Cameras System, A. BibRef

Cao, T.P.[Tam Phuong], Deng, G.[Guang],
Real-Time Vision-Based Stop Sign Detection System on FPGA,
DICTA08(465-471).
IEEE DOI 0812
BibRef

Arlicot, A., Soheilian, B., Paparoditis, N.,
Circular Road Sign Extraction from Street Level Images using Colour, Shape and Texture Database Maps,
CMRT09(205-210).
PDF File. 0909
BibRef

Muhammad, A.S.[Azam Sheikh], Lavesson, N.[Niklas], Davidsson, P.[Paul], Nilsson, M.[Mikael],
Analysis of Speed Sign Classification Algorithms Using Shape Based Segmentation of Binary Images,
CAIP09(1220-1227).
Springer DOI 0909
BibRef

Turan, J., Fifik, M., Ovsenik, L.,
Transform based system for traffic sign recognition,
WSSIP08(441-444).
IEEE DOI 0806
BibRef

Lopez, L.D.[Luis David], Fuentes, O.[Olac],
Color-Based Road Sign Detection and Tracking,
ICIAR07(1138-1147).
Springer DOI 0708
BibRef

Cyganek, B.[Boguslaw],
Object Recognition with the HOSVD of the Multi-model Space-Variant Pattern Tensors,
CAIP11(I: 435-442).
Springer DOI 1109
BibRef
Earlier:
An Analysis of the Road Signs Classification Based on the Higher-Order Singular Value Decomposition of the Deformable Pattern Tensors,
ACIVS10(II: 191-202).
Springer DOI 1012
BibRef
And:
Traffic Scene Segmentation and Robust Filtering for Road Signs Recognition,
ICCVG10(I: 292-299).
Springer DOI 1009
BibRef
Earlier:
A Real-Time Vision System for Traffic Signs Recognition Invariant to Translation, Rotation and Scale,
ACIVS08(xx-yy).
Springer DOI 0810
BibRef
Earlier:
Road-Signs Recognition System for Intelligent Vehicles,
RobVis08(219-233).
Springer DOI 0802
BibRef
Earlier:
Real-Time Detection of the Triangular and Rectangular Shape Road Signs,
ACIVS07(744-755).
Springer DOI 0708
BibRef
And:
Road Signs Recognition by the Scale-Space Template Matching in the Log-Polar Domain,
IbPRIA07(I: 330-337).
Springer DOI 0706
Originally applied to OCR, but more issues for signs.
See also Computational Framework for Family of Order Statistic Filters for Tensor Valued Data. BibRef

Vázquez-Reina, A., López-Sastre, R.J., Siegmann, P., Lafuente-Arroyo, S., Gómez-Moreno, H.,
An Approach to the Recognition of Informational Traffic Signs Based on 2-D Homography and SVMs,
ACIVS06(1163-1173).
Springer DOI 0609
BibRef

Lombardi, L.[Luca], Marmo, R.[Roberto], Toccalini, A.[Andrea],
Automatic Recognition of Road Sign Passo-Carrabile,
CIAP05(1059-1067).
Springer DOI 0509
BibRef

Ballerini, R.[Roberto], Cinque, L.[Luigi], Lombardi, L.[Luca], Marmo, R.[Roberto],
Rectangular Traffic Sign Recognition,
CIAP05(1101-1108).
Springer DOI 0509
BibRef

Silapachote, P., Weinman, J., Hanson, A.R., Mattar, M.A., Weiss, R.,
Automatic Sign Detection and Recognition in Natural Scenes,
VisImpaired05(III: 27-27).
IEEE DOI 0507
BibRef

Silapachote, P.[Piyanuch], Hanson, A.R.[Allen R.], Weiss, R.[Richard],
A Hierarchical Approach to Sign Recognition,
WACV05(I: 22-28).
IEEE DOI 0502
BibRef

Mattar, M.A., Hanson, A.R., Learned-Miller, E.G.,
Sign Classification using Local and Meta-Features,
VisImpaired05(III: 26-26).
IEEE DOI 0507
BibRef

Oh, J.T.[Jun-Taek], Kwak, H.W.[Hyun-Wook], Sohn, Y.H.[Young-Ho], Kim, W.H.[Wook-Hyun],
Segmentation and Recognition of Traffic Signs Using Shape Information,
ISVC05(519-526).
Springer DOI 0512
BibRef

Loy, G., and Barnes, N.M.,
Fast Shape-based Road Sign Detection for a Driver Assistance System,
IROS04(xx-yy). Road sign reader, as seen on CNN and elsewhere. BibRef 0400

Paletta, L.,
Detection of traffic signs using posterior classifier combination,
ICPR02(II: 705-708).
IEEE DOI 0211
BibRef

Vitabile, S., Pollaccia, G., Pilato, G., Sorbello, E.,
Road signs recognition using a dynamic pixel aggregation technique in the HSV color space,
CIAP01(572-577).
IEEE DOI 0210
BibRef

Vitabile, S., Pilato, G., Pullara, F., Sorbello, F.,
A navigation system for vision-guided mobile robots,
CIAP99(566-571).
IEEE DOI 9909
BibRef

Shaposhnikov, D.G., Podladchikova, L.N., Golovan, A.V., Shevtsova, N.A.,
Road Sign Recognition by Single Positioning of Space-Variant Sensor Window,
VI02(213).
PDF File. 0208
BibRef

Bérubé Lauzière, Y.[Yves], Gingras, D.[Denis], Ferrie, F.P.[Frank P.],
A Model-Based Road Sign Identification System,
CVPR01(I:1163-1170).
IEEE DOI 0110
Color, Shape and appearance. BibRef

Schiekel, C.,
A Fast Traffic Sign Recognition Algorithm for Gray Value Images,
CAIP99(588-595).
Springer DOI 9909
BibRef

Janet, J.A., White, M.W., Chase, T.A., Luo, R.C., Sutto, J.C.,
Pattern analysis for autonomous vehicles with the region- and feature-based neural network: global self-localization and traffic sign recognition,
CRA96(IV: 3598-3604). BibRef 9600

Chapter on Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following continues in
Traffic Lights, Objects along the Road, Inspections .