The detection of real-time object has drawn an increased interest in surveillance strategies,
and it is one of the applications of CNNs. This project has focussed on the detection of fire …

Real-time object detection to improve surveillance methods is one of the sought-after
applications of Convolutional Neural Networks (CNNs). This research work has approached …

The increasing proliferation of surveillance cameras to keep an eye on human behavior has
led to a rise in the need for an automated system that can identify violent incidents and …

In recent years, human motion analysis has become the center of video processing,
especially in motion detection and security surveillance. When performing specific tasks, it is …

Recently, the number of violence-related cases in places such as remote roads, pathways,
shopping malls, elevators, sports stadiums, and liquor shops, has increased drastically …

The immense crime rates resulting from using pistols have led governments to seek
solutions to deal with such terrorist incidents. These incidents have a negative impact on …

Due to significant safety concerns, today, many places are filled with CCTV cameras, but it
still uses manual security to overlook these, which leaves much space for human error, be it …

Due to the busy and stressful lifestyle, humans tend to feel frustrated frequently. This harmful
emotional behavior results in violations of several rules, regulations and legislation …

Rising incidents of violence among people in public places is increasing concern in cities
and mostly in highly dense cities of the country. The purpose of this research study is to …

Real-time object detection is one of the most important applications for surveillance and a
prominent computer vision task. This paper proposes a new deep learning-based model for …