Dear Colleagues,

The Special Issue entitled “AI-Enabled Advanced Sensing for Human Action and Activity Recognition” calls for original works revealing the latest research advancements on conventional machine learning and deep learning methods that deeply analyze the structure of human actions and activity patterns from distinct kinds of sensor data or their fusion. These recognition methods need to be based on smart and innovative machine intelligence.

The topics include but are not limited to the following:

• Deep learning for action/activity/anomaly recognition.
• Spatiotemporal features extraction for human sequential patterns analysis.
• Lightweight 2D and 3D convolutional neural networks for human action/activity recognition.
• RGB/depth/skeleton sensors-based action recognition.
• Data prioritization prior to human activity patterns analysis.
• Violence recognition.
• Embedded vision for action/activity recognition.
• Sensors/multi-sensor integrations for activity recognition.
• Activity localization, detection, and context analysis.
• IoT-assisted computationally intelligent methods for activity recognition.
• Cloud/fog computing for action and activity recognition.
• Benchmark datasets for action/activity/anomaly recognition.

SI Link: https://www.mdpi.com/journal/sensors/special_issues/HAAR