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.

Библиографические подробности
Главные авторы:	Morshed, Atique, Siraj, Farhan Md., Munim, Abu Sadat MD., Ayon, Tasnimul Karim, Goni, Saad Rafsan
Другие авторы:	Uddin, Jia
Формат:	Диссертация
Язык:	English
Опубликовано:	Brac University 2021
Предметы:	Deep learning Transfer learning Fault detection RNN LSTM Gammatone Filter Bank Artificial intelligence Cognitive learning theory
Online-ссылка:	http://hdl.handle.net/10361/15759

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