An analysis of artificial intelligence techniques in surveillance video anomaly detection: A comprehensive survey

E Şengönül, R Samet, Q Abu Al-Haija, A Alqahtani… - Applied Sciences, 2023 - mdpi.com
Surveillance cameras have recently been utilized to provide physical security services
globally in diverse private and public spaces. The number of cameras has been increasing …

Amp-net: Appearance-motion prototype network assisted automatic video anomaly detection system

Y Liu, J Liu, K Yang, B Ju, S Liu, Y Wang… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
As essential tools for industry safety protection, automatic video anomaly detection systems
(AVADS) are designed to detect anomalous events of concern in surveillance videos …

Deep learning for abnormal human behavior detection in surveillance videos—A survey

LM Wastupranata, SG Kong, L Wang - Electronics, 2024 - mdpi.com
Detecting abnormal human behaviors in surveillance videos is crucial for various domains,
including security and public safety. Many successful detection techniques based on deep …

Anomaly detection in surveillance videos: a thematic taxonomy of deep models, review and performance analysis

S Chandrakala, K Deepak, G Revathy - Artificial Intelligence Review, 2023 - Springer
The task of anomaly detection has recently gained much attention in the field of visual
surveillance. Video surveillance data is often available in large quantities, but manual …

Bi-READ: Bi-Residual AutoEncoder based feature enhancement for video anomaly detection

R Kommanduri, M Ghorai - Journal of Visual Communication and Image …, 2023 - Elsevier
Video anomaly detection (VAD) refers to identifying abnormal events in the surveillance
video. Typically, reconstruction based video anomaly detection techniques employ …

A new unsupervised video anomaly detection using multi-scale feature memorization and multipath temporal information prediction

N Taghinezhad, M Yazdi - IEEE Access, 2023 - ieeexplore.ieee.org
Anomaly detection in video is an advanced computer vision challenge that recognizes video
segments containing out-of-the-ordinary motions or objects. Most recent techniques in video …

COVAD: Content-oriented video anomaly detection using a self attention-based deep learning model

W Shao, P Rajapaksha, Y Wei, D Li, N Crespi… - Virtual Reality & …, 2023 - Elsevier
Background Video anomaly detection has always been a hot topic and has attracted
increasing attention. Many of the existing methods for video anomaly detection depend on …

[HTML][HTML] Video anomaly detection using cross u-net and cascade sliding window

Y Kim, JY Yu, E Lee, YG Kim - Journal of King Saud University-Computer …, 2022 - Elsevier
As video surveillance exponentially increases, a method that automatically detects abnormal
events in video surveillance is essential. Several anomaly detection methods have been …

Texture classification-based feature processing for violence-based anomaly detection in crowded environments

AA Mohamed, F Alqahtani, A Shalaby… - Image and vision …, 2022 - Elsevier
Anomaly detection from video surveillance inputs helps to improve security in crowded
places and outdoors. The captured image is analyzed to identify human faces, objects, and …

Machine-learning-assisted and real-time-feedback-controlled growth of InAs/GaAs quantum dots

C Shen, W Zhan, K **n, M Li, Z Sun, H Cong… - Nature …, 2024 - nature.com
The applications of self-assembled InAs/GaAs quantum dots (QDs) for lasers and single
photon sources strongly rely on their density and quality. Establishing the process …