Name: Spatio-Temporal Human Activity Recognition using CNN and LSTM (en Inglés)
Price: 62.09 USD
Availability: InStock
Author: Chatterjee, Tarunima; Acharjya, Pinaki Pratim
ISBN: 9786209136832

portada Spatio-Temporal Human Activity Recognition using CNN and LSTM (en Inglés)

Spatio-Temporal Human Activity Recognition using CNN and LSTM (en Inglés)

Formato

Libro Físico

Editorial

LAP Lambert Academic Publishing

Autor

Chatterjee, Tarunima; Acharjya, Pinaki Pratim

Idioma

Inglés

N° páginas

Encuadernación

Tapa Blanda

Dimensiones

22.9 x 15.2 x 0.4 cm

ISBN13

9786209136832

Spatio-Temporal Human Activity Recognition using CNN and LSTM (en Inglés)

Chatterjee, Tarunima; Acharjya, Pinaki Pratim (Autor) · LAP Lambert Academic Publishing · Tapa Blanda

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Reseña del libro "Spatio-Temporal Human Activity Recognition using CNN and LSTM (en Inglés)"

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.