This book presents a robust Human Activity Recognition (HAR) system that integrates Convolutional Neural Networks (CNNs) with Long Short-Term Memory (LSTM) networks, evaluated on the challenging UCF50 dataset. By combining CNNs' ability to extract spatial features from video frames with LSTMs' strength in modeling temporal sequences, the hybrid model accurately recognizes both simple and complex human actions unfolding over time. This approach addresses key HAR challenges, improving accuracy and generalization across diverse activities. Experimental results demonstrate enhanced precision and...
This book presents a robust Human Activity Recognition (HAR) system that integrates Convolutional Neural Networks (CNNs) with Long Short-Term Memory (...
