Automated surveillance systems observe the environment utilizing cameras. The observed
scenario is then analysed using motion detection, crowd behaviour, individual behaviour …

Nowadays, Human Activity Recognition (HAR) is being widely used in a variety of domains,
and vision and sensor-based data enable cutting-edge technologies to detect, recognize …

In action recognition, although the combination of spatio-temporal videos and skeleton
features can improve the recognition performance, a separate model and balancing feature …

To understand the real world using various types of data, Artificial Intelligence (AI) is the
most used technique nowadays. While finding the pattern within the analyzed data …

Multimodal action recognition techniques combine several image modalities (RGB, Depth,
Skeleton, and InfraRed) for a more robust recognition. According to the fusion level in the …

Analyzing videos and images captured by unmanned aerial vehicles or aerial drones is an
emerging application attracting significant attention from researchers in various areas of …

Action recognition is a major branch of computer vision research. As a widely used
technology, action recognition has been applied to human–computer interaction, intelligent …

Human Action Recognition (HAR) is an active research topic in machine learning for the last
few decades. Visual surveillance, robotics, and pedestrian detection are the main …

Temporal convolutions have been the paradigm of choice in action segmentation, which
enhances long-term receptive fields by increasing convolution layers. However, deep …

Deep neural networks (DNNs) have achieved tremendous success in various applications
including video action recognition, yet remain vulnerable to backdoor attacks (Trojans). The …