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.

Détails bibliographiques
Auteurs principaux:	Pranta, Kazi Al Refat, Islam, Fahad Mohammad Rejwanul, Ahmed, Khandakar Fahim, Saha, Prince, Rahman, Naimur
Autres auteurs:	Reza, Tanzim
Format:	Thèse
Langue:	English
Publié:	Brac University 2024
Sujets:	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)
Accès en ligne:	http://hdl.handle.net/10361/22890

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