A New Efficient Hybrid Technique for Human Action Recognition Using 2D Conv-RBM and LSTM with Optimized Frame Selection

A New Efficient Hybrid Technique for Human Action Recognition Using 2D Conv-RBM and LSTM with Optimized Frame Selection

Recognizing human actions through video analysis has gained significant attention in applications like surveillance, sports analytics, and human–computer interaction. While deep learning models such as 3D convolutional neural networks (CNNs) and recurrent neural networks (RNNs) deliver promising res...

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Bibliographic Details
Main Authors: Majid Joudaki, Mehdi Imani, Hamid R. Arabnia
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Technologies
Subjects:
action recognition
convolutional restricted Boltzmann machine
long short-term memory
spatial–temporal feature extraction
video processing
Online Access:https://www.mdpi.com/2227-7080/13/2/53

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https://www.mdpi.com/2227-7080/13/2/53

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