Human Action Recognition by Learning Spatio-Temporal Features with Deep Neural Networks

Human Action Recognition by Learning Spatio-Temporal Features with Deep Neural Networks

Human action recognition plays a crucial role in various applications, including video surveillance, human-computer interaction, and activity analysis. This paper presents a study on human action recognition by leveraging CNN-LSTM architecture with an attention model. The proposed approach aims to c...

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Bibliographic Details
Main Authors: Haindavi P., Sharif Shaik, Lakshman A., Aerranagula Veerender, Reddy P. Chandra Sekhar, Kumar Anuj
Format: Article
Language:English
Published: EDP Sciences 2023-01-01
Series:E3S Web of Conferences
Subjects:
cnn-lstm
deep learning
recognize human action
Online Access:https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/67/e3sconf_icmpc2023_01154.pdf

Internet

https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/67/e3sconf_icmpc2023_01154.pdf

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