A texture based industrial fault diagnosis model using Gammatone Filter Bank and transfer learning

A texture based industrial fault diagnosis model using Gammatone Filter Bank and transfer learning

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.

Bibliografiset tiedot
Päätekijät: Morshed, Atique, Siraj, Farhan Md., Munim, Abu Sadat MD., Ayon, Tasnimul Karim, Goni, Saad Rafsan
Muut tekijät: Uddin, Jia
Aineistotyyppi: Opinnäyte
Kieli:English
Julkaistu: Brac University 2021
Aiheet:
Deep learning
Transfer learning
Fault detection
RNN
LSTM
Gammatone Filter Bank
Artificial intelligence
Cognitive learning theory
Linkit:http://hdl.handle.net/10361/15759

Internet

http://hdl.handle.net/10361/15759

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