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.

Detalles Bibliográficos
Autores principales:	Pranta, Kazi Al Refat, Islam, Fahad Mohammad Rejwanul, Ahmed, Khandakar Fahim, Saha, Prince, Rahman, Naimur
Otros Autores:	Reza, Tanzim
Formato:	Tesis
Lenguaje:	English
Publicado:	Brac University 2024
Materias:	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)
Acceso en línea:	http://hdl.handle.net/10361/22890

http://hdl.handle.net/10361/22890

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