H. S. Ganesha

A Lightweight CNN-GRU Model for Human Activity Recognition with Efficient Edge Deployment Using TFLite

A resource-constrained CNN-GRU hybrid model for HAR on the WISDM dataset that uses convolutional layers for spatial learning and gated recurrent units (GRU) for sequence learning, enabling real-time HAR on edge devices.