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

Internet

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

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