Mohammad F Alfridi

A deep-learning based gait classification and anomaly detection framework for healthcare surveillance.

A unified framework that combines three complementary components: transformer-based temporal modeling to capture both short-term and long-term gait dynamics, lightweight architectures for efficient deployment on edge devices, and federated learning for privacy-preserving distributed training without requiring raw data...