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portada Spatio-Temporal Human Activity Recognition using CNN and LSTM
Type
Physical Book
Publisher
Author
Language
English
Pages
68
Format
Paperback
Dimensions
22.9x15.2x0.4 cm
ISBN13
9786209136832

Spatio-Temporal Human Activity Recognition using CNN and LSTM

Chatterjee, Tarunima; Acharjya, Pinaki Pratim (Author) · LAP Lambert Academic Publishing · Paperback

Spatio-Temporal Human Activity Recognition using CNN and LSTM - Chatterjee, Tarunima; Acharjya, Pinaki Pratim

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Synopsis "Spatio-Temporal Human Activity Recognition using CNN and LSTM"

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 stability over conventional models. The system's versatility supports applications in surveillance, healthcare, sports analytics, and human-computer interaction. By bridging spatial and temporal learning, the book offers a scalable, real-world HAR solution adaptable to various environments, laying groundwork for future advances in activity recognition technologies.

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