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.

Bibliografiska uppgifter
Huvudupphovsmän: Morshed, Atique, Siraj, Farhan Md., Munim, Abu Sadat MD., Ayon, Tasnimul Karim, Goni, Saad Rafsan
Övriga upphovsmän: Uddin, Jia
Materialtyp: Lärdomsprov
Språk:English
Publicerad: Brac University 2021
Ämnen:
Deep learning
Transfer learning
Fault detection
RNN
LSTM
Gammatone Filter Bank
Artificial intelligence
Cognitive learning theory
Länkar:http://hdl.handle.net/10361/15759

Internet

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

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