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

Internet

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

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