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.

Podrobná bibliografie
Hlavní autoři: Morshed, Atique, Siraj, Farhan Md., Munim, Abu Sadat MD., Ayon, Tasnimul Karim, Goni, Saad Rafsan
Další autoři: Uddin, Jia
Médium: Diplomová práce
Jazyk:English
Vydáno: Brac University 2021
Témata:
Deep learning
Transfer learning
Fault detection
RNN
LSTM
Gammatone Filter Bank
Artificial intelligence
Cognitive learning theory
On-line přístup:http://hdl.handle.net/10361/15759

Internet

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

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