Deep learning has recently gained popularity in the field of video anomaly detection, with
the development of various methods for identifying abnormal events in visual data. The …

This work introduces an unsupervised framework for video anomaly detection, leveraging a
hybrid deep learning model that combines a vision transformer (ViT) with a convolutional …

The use of surveillance cameras is a common solution that addresses the need to provide
security and manage urban traffic that arises due to the increasing population in cities. As …

Hybrid vehicles are pivotal in transitioning to sustainable transportation, but effective energy
management is challenged by data contamination. This paper proposes a novel approach …

The widespread adoption of video surveillance systems in public security and network
security domains has underscored the importance of video anomaly detection as a pivotal …

In crowded environments, the importance of automatic video surveillance cannot be
overstated. It plays a vital role in detecting unusual incidents and averting accidents …

This paper proposes an efficient lightweight deep spatial residual autoencoder (SRAE)
model to detect anomalous events in video surveillance systems. A lightweight network is …

Deep learning has recently gained popularity in the field of video anomaly detection, with
the development of various methods for identifying abnormal events in visual data. The …