Leveraging sequential deep learning models for detecting multitude of human action categories

Leveraging sequential deep learning models for detecting multitude of human action categories

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023.

Detalhes bibliográficos
Main Authors: Pranta, Kazi Al Refat, Islam, Fahad Mohammad Rejwanul, Ahmed, Khandakar Fahim, Saha, Prince, Rahman, Naimur
Outros Autores: Reza, Tanzim
Formato: Thesis
Idioma:English
Publicado em: Brac University 2024
Assuntos:
Human action recognition
Intelligent decision-making
Recurrent neural network (RNN)
Machine learning
Convolutional long short-term memory
Deep learning (Machine learning)
Neural networks (Computer science)
Cognitive learning theory (Deep learning)
Acesso em linha:http://hdl.handle.net/10361/22890

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