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.

Xehetasun bibliografikoak
Egile Nagusiak: Pranta, Kazi Al Refat, Islam, Fahad Mohammad Rejwanul, Ahmed, Khandakar Fahim, Saha, Prince, Rahman, Naimur
Beste egile batzuk: Reza, Tanzim
Formatua: Thesis
Hizkuntza:English
Argitaratua: Brac University 2024
Gaiak:
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)
Sarrera elektronikoa:http://hdl.handle.net/10361/22890

Internet

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

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