Video surveillance systems are popular and used in public places such as market places,
shop** malls, hospitals, banks, streets, education institutions, city administrative offices …

As aquaculture continues to grow and intensify, there is an increasing public concern over
the welfare of farmed fish. Stress and production‐related pathologies and repressed growth …

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 …

Detecting anomalies in videos is a fundamental issue in public security. The majority of
existing deep learning methods often perform anomaly detection based on the behavior or …

Deep learning models have been widely used for anomaly detection in surveillance videos.
Typical models are equipped with the capability to reconstruct normal videos and evaluate …

Since criminals may engage in a wide variety of crime scenes in public spaces, the time
immediately before and after these events must be monitored. As a rule, there will be …

In this paper, a novel approach to abnormal event detection in crowded scenes is presented
based on a new low-rank and compact coefficient dictionary learning (LRCCDL) algorithm …

Crowd anomaly detection is a key research area in vision-based surveillance. Most of the
crowd anomaly detection algorithms are either too slow, bulky, or power-hungry to be …

In this paper, a new method for detecting abnormal events in public surveillance systems is
proposed. In the first step of the proposed method, candidate regions are extracted, and the …

Suspicious pre-and post-activity detection in crowded places is essential as many
suspicious activities may be carried out by culprits. Usually, there will be installations of …