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.

Dettagli Bibliografici
Autori principali:	Morshed, Atique, Siraj, Farhan Md., Munim, Abu Sadat MD., Ayon, Tasnimul Karim, Goni, Saad Rafsan
Altri autori:	Uddin, Jia
Natura:	Tesi
Lingua:	English
Pubblicazione:	Brac University 2021
Soggetti:	Deep learning Transfer learning Fault detection RNN LSTM Gammatone Filter Bank Artificial intelligence Cognitive learning theory
Accesso online:	http://hdl.handle.net/10361/15759

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