In the era of smart cities, the role of surveillance systems in ensuring community safety and
environmental sustainability has become increasingly significant. Traditional surveillance …

With the dramatic increase in video surveillance applications and public safety measures,
the need for an accurate and effective system for abnormal/suspicious activity classification …

Since the advent of visual sensors, smart cities have generated massive surveillance video
data, which can be intelligently inspected to detect anomalies. Computer vision-based …

Automatic anomaly detection plays a critical role in surveillance systems but requires
datasets comprising large amounts of annotated data to train and evaluate models …

Surveillance videos play an important role in ensuring the safety and security of public and
private spaces, buildings, and critical infrastructure. However, manually monitoring these …

With the dramatic increase in video surveillance applications and public safety measures,
the need for an accurate and effective system for abnormal/sus-picious activity classification …

Autonomous anomaly detection is a fundamental step in visual surveillance systems, and so
we have witnessed great progress in the form of various promising algorithms. Nonetheless …

The current concept of smart cities influences urban planners and researchers to provide
modern, secured and sustainable infrastructure and gives a decent quality of life to its …

Crowded-environment anomaly detection is crucial for public safety, surveillance, and crowd
management. Traditional anomaly detection algorithms struggle with congested scenes …

How to automatically monitor wide critical open areas is a challenge to be addressed.
Recent computer vision algorithms can be exploited to avoid the deployment of a large …