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Springer DOI
1408
BibRef
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IEEE DOI
1405
greedy algorithms
Transportation domain to identify unusual patterns such as traffic
violations, accidents, unsafe driver behavior, street crime, and other
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BibRef
Yuan, Y.,
Wang, D.,
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Anomaly Detection in Traffic Scenes via Spatial-Aware Motion
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ITS(18), No. 5, May 2017, pp. 1198-1209.
IEEE DOI
1705
Bayes methods, Dictionaries, Image reconstruction, Optical imaging,
Robustness, Vehicles, Videos, anomaly detection,
crowded scenes, motion analysis, sparse reconstruction, video, analysis
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ITS(18), No. 8, August 2017, pp. 2260-2270.
IEEE DOI
1708
Accidents, Data mining, Data models, Data visualization, Roads,
Vehicles, Visual analytics, Anomaly detection,
intelligent transport systems, normal traffic model, visual, analytics
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Alfeo, A.L.,
Cimino, M.G.C.A.[M. G. C. A.],
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ITS(19), No. 7, July 2018, pp. 2258-2267.
IEEE DOI
1807
Computational modeling, Global Positioning System, Pollution,
Pollution measurement, Public transportation, Urban areas,
taxi-GPS traces
BibRef
Kalamaras, I.,
Zamichos, A.,
Salamanis, A.,
Drosou, A.,
Kehagias, D.D.,
Margaritis, G.,
Papadopoulos, S.,
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An Interactive Visual Analytics Platform for Smart Intelligent
Transportation Systems Management,
ITS(19), No. 2, February 2018, pp. 487-496.
IEEE DOI
1802
Anomaly detection, Data visualization, Roads, Tools,
Visual analytics, Traffic prediction, hypothesis testing,
visual analytics
BibRef
Xu, M.,
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Anomaly Detection in Road Networks Using Sliding-Window Tensor
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ITS(20), No. 12, December 2019, pp. 4704-4713.
IEEE DOI
2001
Roads, Anomaly detection, Trajectory,
Anomaly detection, tensor factorization, sliding window, trajectory data
BibRef
Santhosh, K.K.,
Dogra, D.P.,
Roy, P.P.,
Anomaly Detection in Road Traffic Using Visual Surveillance: A Survey,
Surveys(53), No. 6, December 2020, pp. xx-yy.
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2103
Learning methods, classification, road traffic analysis
BibRef
Cao, W.[Wen],
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Wu, Q.[Qisheng],
Joint Tracking and Identification Based on Constrained Joint Decision
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ITS(22), No. 10, October 2021, pp. 6489-6502.
IEEE DOI
2110
Violation detection and treatment.
Target tracking, Roads, Estimation, Automobiles, Couplings,
Mathematical model, Joint tracking and identification,
joint performance metric
BibRef
Forti, N.[Nicola],
d'Afflisio, E.[Enrica],
Braca, P.[Paolo],
Millefiori, L.M.[Leonardo M.],
Willett, P.[Peter],
Carniel, S.[Sandro],
Maritime Anomaly Detection in a Real-World Scenario:
Ever Given Grounding in the Suez Canal,
ITS(23), No. 8, August 2022, pp. 13904-13910.
IEEE DOI
2208
Marine vehicles, Artificial intelligence, Irrigation,
Anomaly detection, Grounding, Containers, Testing,
statistical hypothesis testing
BibRef
Yao, Y.[Yu],
Wang, X.[Xizi],
Xu, M.Z.[Ming-Ze],
Pu, Z.L.[Ze-Lin],
Wang, Y.C.[Yu-Chen],
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Crandall, D.J.[David J.],
DoTA: Unsupervised Detection of Traffic Anomaly in Driving Videos,
PAMI(45), No. 1, January 2023, pp. 444-459.
IEEE DOI
2212
Videos, Measurement, Cameras, Annotations, Benchmark testing,
Anomaly detection, Accidents, Video anomaly detection,
Video action recognition
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Kant, K.[Krishna],
Pal, A.[Amitangshu],
C-FAR: A Compositional Framework for Anomaly Resolution in
Intelligent Transportation Systems,
ITS(24), No. 1, January 2023, pp. 1015-1024.
IEEE DOI
2301
Roads, Deep learning, Anomaly detection, Monitoring, Calculus, Safety,
Intelligent transportation systems,
combinatorial optimization
BibRef
Han, X.S.[Xing-Shuo],
Zhou, Y.[Yuan],
Chen, K.J.[Kang-Jie],
Qiu, H.[Han],
Qiu, M.[Meikang],
Liu, Y.[Yang],
Zhang, T.W.[Tian-Wei],
ADS-Lead: Lifelong Anomaly Detection in Autonomous Driving Systems,
ITS(24), No. 1, January 2023, pp. 1039-1051.
IEEE DOI
2301
Anomaly detection, Global Positioning System, Location awareness,
Autonomous vehicles, Transformers, Data models, Collaboration,
cognitive networking
BibRef
Farahnakian, F.[Farshad],
Nicolas, F.[Florent],
Farahnakian, F.[Fahimeh],
Nevalainen, P.[Paavo],
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Raduly-Baka, C.[Csaba],
A Comprehensive Study of Clustering-Based Techniques for Detecting
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2304
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Zhao, S.[Shuai],
Zhao, D.X.[Da-Xing],
Liu, R.Q.[Rui-Qiang],
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Chen, B.[Bo],
Chen, J.L.[Jun-Liang],
GMAT-DU: Traffic Anomaly Prediction With Fine Spatiotemporal
Granularity in Sparse Data,
ITS(24), No. 11, November 2023, pp. 13503-13517.
IEEE DOI
2311
BibRef
Mansourian, P.[Pegah],
Zhang, N.[Ning],
Jaekel, A.[Arunita],
Kneppers, M.[Marc],
Deep Learning-Based Anomaly Detection for Connected Autonomous
Vehicles Using Spatiotemporal Information,
ITS(24), No. 12, December 2023, pp. 16006-16017.
IEEE DOI
2312
BibRef
Chen, J.Z.[Jun-Zhou],
Pu, J.J.[Jia-Jun],
Yin, B.[Baiqiao],
Zhang, R.H.[Rong-Hui],
Wu, J.J.[Jun Jie],
TA-NET: Empowering Highly Efficient Traffic Anomaly Detection Through
Multi-Head Local Self-Attention and Adaptive Hierarchical Feature
Reconstruction,
ITS(25), No. 9, September 2024, pp. 12372-12384.
IEEE DOI
2409
Feature extraction, Anomaly detection, Task analysis,
Hidden Markov models, Supervised learning, Benchmark testing, transformer
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Gu, K.[Ke],
OuYang, X.[Xin],
Wang, Y.[Yi],
Malicious Vehicle Detection Scheme Based on Spatio-Temporal Features
of Traffic Flow Under Cloud-Fog Computing-Based IoVs,
ITS(25), No. 9, September 2024, pp. 11534-11551.
IEEE DOI
2409
Feature extraction, Cloud computing, Servers, Roads,
Vehicle detection, Predictive models, Correlation, reputation
BibRef
Zhao, Y.X.[Yu-Xiang],
Wu, W.H.[Wen-Hao],
He, Y.[Yue],
Li, Y.Y.[Ying-Ying],
Tan, X.[Xiao],
Chen, S.F.[Shi-Feng],
Practices and A Strong Baseline for Traffic Anomaly Detection,
AICity21(3988-3996)
IEEE DOI
2109
Tracking, Vehicle detection, Urban areas, Dynamics, Transportation,
Spatiotemporal phenomena, Automobiles
BibRef
Chen, J.Y.[Jing-Yuan],
Ding, G.C.[Guan-Chen],
Yang, Y.C.[Yu-Chen],
Han, W.W.[Wen-Wei],
Xu, K.M.[Kang-Min],
Gao, T.Y.[Tian-Yi],
Zhang, Z.[Zhe],
Ouyang, W.P.[Wan-Ping],
Cai, H.[Hao],
Chen, Z.Z.[Zhen-Zhong],
Dual-Modality Vehicle Anomaly Detection via Bilateral Trajectory
Tracing,
AICity21(4011-4020)
IEEE DOI
2109
Backtracking, Tracking, Urban areas, Static analysis, Trajectory,
Artificial intelligence, Vehicle dynamics
BibRef
Wu, J.[Jie],
Wang, X.H.[Xiong-Hui],
Xiao, X.F.[Xue-Feng],
Wang, Y.T.[Yi-Tong],
Box-Level Tube Tracking and Refinement for Vehicles Anomaly Detection,
AICity21(4107-4113)
IEEE DOI
2109
Urban areas, Transportation,
Artificial intelligence, Vehicle dynamics, Task analysis
BibRef
Doshi, K.[Keval],
Yilmaz, Y.[Yasin],
An Efficient Approach for Anomaly Detection in Traffic Videos,
AICity21(4231-4239)
IEEE DOI
2109
Performance evaluation, Temperature, Computational modeling,
Image edge detection, Urban areas, Training data, Artificial intelligence
BibRef
Aboah, A.[Armstrong],
Shoman, M.[Maged],
Mandal, V.[Vishal],
Davami, S.[Sayedomidreza],
Adu-Gyamfi, Y.[Yaw],
Sharma, A.[Anuj],
A Vision-based System for Traffic Anomaly Detection using Deep
Learning and Decision Trees,
AICity21(4202-4207)
IEEE DOI
2109
Deep learning, Adaptation models, Roads, Estimation,
Real-time systems, Pattern recognition
BibRef
Singh, H.,
Hand, E.M.,
Alexis, K.[Kostas],
Anomalous Motion Detection On Highway Using Deep Learning,
ICIP20(1901-1905)
IEEE DOI
2011
Videos, Anomaly detection, Training, Predictive models,
Optical imaging, Road transportation, Adaptive optics,
oneclass classification
BibRef
Shine, L.[Linu],
Vaishnav, M.A.,
Jiji, C.V.,
Fractional Data Distillation Model for Anomaly Detection in Traffic
Videos,
City20(2581-2589)
IEEE DOI
2008
Videos, Detectors, Data models, Anomaly detection,
Hidden Markov models, Roads, Urban areas
BibRef
Li, Y.,
Wu, J.,
Bai, X.,
Yang, X.,
Tan, X.,
Li, G.,
Wen, S.,
Zhang, H.,
Ding, E.,
Multi-Granularity Tracking with Modularlized Components for
Unsupervised Vehicles Anomaly Detection,
City20(2501-2510)
IEEE DOI
2008
Anomaly detection, Roads, Task analysis, Tracking, Training,
Artificial intelligence, Urban areas
BibRef
Tran, M.T.[Minh-Triet],
Nguyen, T.V.[Tam V.],
Hoang, T.H.[Trung-Hieu],
Le, T.N.[Trung-Nghia],
Nguyen, K.T.[Khac-Tuan],
Dinh, D.T.[Dat-Thanh],
Nguyen, T.A.[Thanh-An],
Nguyen, H.D.[Hai-Dang],
Hoang, X.N.[Xuan-Nhat],
Nguyen, T.T.[Trong-Tung],
Vo-Ho, V.K.[Viet-Khoa],
Do, T.L.[Trong-Le],
Nguyen, L.[Lam],
Le, M.Q.[Minh-Quan],
Nguyen-Dinh, H.P.[Hoang-Phuc],
Pham, T.T.[Trong-Thang],
Nguyen, X.V.[Xuan-Vy],
Nguyen, E.R.[E-Ro],
Tran, Q.C.[Quoc-Cuong],
Tran, H.[Hung],
Dao, H.[Hieu],
Tran, M.K.[Mai-Khiem],
Nguyen, Q.T.[Quang-Thuc],
Nguyen, T.P.[Tien-Phat],
Vu-Le, T.A.[The-Anh],
Diep, G.H.[Gia-Han],
Do, M.N.[Minh N.],
iTASK - Intelligent Traffic Analysis Software Kit,
City20(2607-2616)
IEEE DOI
2008
Tracking, Urban areas, Anomaly detection, Artificial intelligence,
Detectors, Task analysis, Event detection
BibRef
Doshi, K.,
Yilmaz, Y.,
Fast Unsupervised Anomaly Detection in Traffic Videos,
City20(2658-2664)
IEEE DOI
2008
Videos, Anomaly detection, Object detection,
Computational modeling, Training, Real-time systems, Benchmark testing
BibRef
Wei, J.,
Zhao, J.,
Zhao, Y.,
Zhao, Z.,
Unsupervised Anomaly Detection for Traffic Surveillance Based on
Background Modeling,
City18(129-1297)
IEEE DOI
1812
Videos, Anomaly detection, Surveillance, Accidents, Training data,
Task analysis
BibRef
Chang, M.,
Wei, Y.,
Song, N.,
Lyu, S.,
Video Analytics in Smart Transportation for the AIC'18 Challenge,
City18(61-617)
IEEE DOI
1812
Cameras, Estimation, Radar tracking, Calibration, Tracking,
Anomaly detection, Vehicle crash testing
BibRef
Xu, Y.[Yan],
Xi, O.Y.[Ou-Yang],
Cheng, Y.[Yu],
Yu, S.N.[Shi-Ning],
Xiong, L.[Lin],
Ng, C.C.[Choon-Ching],
Pranata, S.[Sugiri],
Shen, S.M.[Sheng-Mei],
Xing, J.L.[Jun-Liang],
Dual-Mode Vehicle Motion Pattern Learning for High Performance Road
Traffic Anomaly Detection,
City18(145-1457)
IEEE DOI
1812
Roads, Automobiles, Anomaly detection, Vehicle dynamics,
Analytical models, Tracking, Surveillance
BibRef
Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Traffic Control, Traffic Analysis, Not Image Analysis .