A Hybrid Feature Selection Method for Human Activity Recognition

Human Activity Recognition (HAR) is a highly active research field, as it is essential in various domains such as healthcare, surveillance, sports, robotics, etc. Many HAR systems are based on Machine Learning (ML) algorithms. However, deploying these systems is often a significant challenge due to their spatial and temporal complexity, especially in real-time applications where quasi-instantaneou...