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.

書誌詳細
主要な著者:	Morshed, Atique, Siraj, Farhan Md., Munim, Abu Sadat MD., Ayon, Tasnimul Karim, Goni, Saad Rafsan
その他の著者:	Uddin, Jia
フォーマット:	学位論文
言語:	English
出版事項:	Brac University 2021
主題:	Deep learning Transfer learning Fault detection RNN LSTM Gammatone Filter Bank Artificial intelligence Cognitive learning theory
オンライン･アクセス:	http://hdl.handle.net/10361/15759

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