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.

Bibliographische Detailangaben
Hauptverfasser:	Morshed, Atique, Siraj, Farhan Md., Munim, Abu Sadat MD., Ayon, Tasnimul Karim, Goni, Saad Rafsan
Weitere Verfasser:	Uddin, Jia
Format:	Abschlussarbeit
Sprache:	English
Veröffentlicht:	Brac University 2021
Schlagworte:	Deep learning Transfer learning Fault detection RNN LSTM Gammatone Filter Bank Artificial intelligence Cognitive learning theory
Online Zugang:	http://hdl.handle.net/10361/15759

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