Drones connected via the web are increasingly being used for crowd anomaly detection
(CAD). Existing solutions, however, face many challenges, such as low accuracy and high …

Crowd anomaly detection is one of the most popular topics in computer vision in the context
of smart cities. A plethora of deep learning methods have been proposed that generally …

This study proposed an AlexNet-based crowd anomaly detection model in the video (image
frames). The proposed model was comprised of four convolution layers (CLs) and three …

Abnormal event detection in video surveillance is extremely important, especially for
crowded scenes. In recent years, many algorithms have been proposed based on hand …

Intelligent identification of abnormal behaviors in crowd scenes enables far more efficient
development of smart cities. In recent approaches, abnormalities are detected using an …

Detecting anomalies in crowd scenes holds a critical task in automated video inspection to
prevent any casualties in the regions that witness the higher quantity of footfalls. The main …

Abnormal event detection is one of the most challenging tasks in computer vision. Many
existing deep anomaly detection models are based on reconstruction errors, where the …

Anomaly detection within crowded environments is a key challenge in the computer vision
and crowd behaviour understanding fields. Furthermore, anomaly detection within high …

In surveillance video, crowd anomaly detection uses humans' position and orientation
deviation. Encoding these positions is complicated and uses manual or handcrafted features …

Crowd anomaly detection is a practical and challenging problem to computer vision and
VideoGIS due to abnormal events' rare and diverse nature. Consequently, traditional …