Anomaly detection in road traffic using visual surveillance: A survey

KK Santhosh, DP Dogra, PP Roy - ACM Computing Surveys (CSUR), 2020 - dl.acm.org
Computer vision has evolved in the last decade as a key technology for numerous
applications replacing human supervision. Timely detection of traffic violations and …

Edge intelligence: Architectures, challenges, and applications

D Xu, T Li, Y Li, X Su, S Tarkoma, T Jiang… - arxiv preprint arxiv …, 2020 - arxiv.org
Edge intelligence refers to a set of connected systems and devices for data collection,
caching, processing, and analysis in locations close to where data is captured based on …

Edge intelligence: Empowering intelligence to the edge of network

D Xu, T Li, Y Li, X Su, S Tarkoma, T Jiang… - Proceedings of the …, 2021 - ieeexplore.ieee.org
Edge intelligence refers to a set of connected systems and devices for data collection,
caching, processing, and analysis proximity to where data are captured based on artificial …

Deep-anomaly: Fully convolutional neural network for fast anomaly detection in crowded scenes

M Sabokrou, M Fayyaz, M Fathy, Z Moayed… - Computer Vision and …, 2018 - Elsevier
The detection of abnormal behaviour in crowded scenes has to deal with many challenges.
This paper presents an efficient method for detection and localization of anomalies in …

RWF-2000: an open large scale video database for violence detection

M Cheng, K Cai, M Li - 2020 25th International Conference on …, 2021 - ieeexplore.ieee.org
In recent years, surveillance cameras are widely deployed in public places, and the general
crime rate has been reduced significantly due to these ubiquitous devices. Usually, these …

Learning deep event models for crowd anomaly detection

Y Feng, Y Yuan, X Lu - Neurocomputing, 2017 - Elsevier
Abnormal event detection in video surveillance is extremely important, especially for
crowded scenes. In recent years, many algorithms have been proposed based on hand …

RETRACTED: Efficient anomaly detection in surveillance videos based on multi layer perception recurrent neural network

M Murugesan, S Thilagamani - 2020 - Elsevier
RETRACTED: Efficient anomaly detection in surveillance videos based on multi layer perception
recurrent neural network - ScienceDirect Skip to main contentSkip to article Elsevier logo …

Revisiting crowd behaviour analysis through deep learning: Taxonomy, anomaly detection, crowd emotions, datasets, opportunities and prospects

FL Sánchez, I Hupont, S Tabik, F Herrera - Information Fusion, 2020 - Elsevier
Crowd behaviour analysis is an emerging research area. Due to its novelty, a proper
taxonomy to organise its different sub-tasks is still missing. This paper proposes a taxonomic …

Crowd anomaly detection using aggregation of ensembles of fine-tuned convnets

K Singh, S Rajora, DK Vishwakarma, G Tripathi… - Neurocomputing, 2020 - Elsevier
Anomaly detection in crowded scenes plays a crucial role in automatic video surveillance to
avert any casualty in the areas witnessing the high amount of footfalls. The key challenge for …

Unsupervised anomaly detection and localization based on deep spatiotemporal translation network

T Ganokratanaa, S Aramvith, N Sebe - IEEE Access, 2020 - ieeexplore.ieee.org
Anomaly detection is of great significance for intelligent surveillance videos. Current works
typically struggle with object detection and localization problems due to crowded and …