Simple Summary Skin cancer is a major concern worldwide, and accurately identifying it is
crucial for effective treatment. we propose a modified deep learning model called …

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 …

Individual abnormal behaviors vary depending on crowd sizes, contexts, and scenes.
Challenges such as partial occlusions, blurring, a large number of abnormal behaviors, and …

Object detection using deep learning has attracted considerable interest from researchers
because of its competency in performing state-of-the-art tasks, including detection …

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 …

The continuous development of intelligent video surveillance systems has increased the
demand for enhanced vision-based methods of automated detection of anomalies within …

Crowding at the entrances of large events may lead to critical and life-threatening situations,
particularly when people start pushing each other to reach the event faster. Automatic and …

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 …

Recognizing and localizing anomalous events in crowd scenes is a challenging problem
that has attracted the attention of researchers in computer vision. Surveillance cameras …

With the increasing number of video surveillance cameras in public buildings, it has become
challenging, yet significant to detect abnormal pedestrian behaviors in crowd management …