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.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Morshed, Atique, Siraj, Farhan Md., Munim, Abu Sadat MD., Ayon, Tasnimul Karim, Goni, Saad Rafsan
Άλλοι συγγραφείς: Uddin, Jia
Μορφή: Thesis
Γλώσσα:English
Έκδοση: Brac University 2021
Θέματα:
Deep learning
Transfer learning
Fault detection
RNN
LSTM
Gammatone Filter Bank
Artificial intelligence
Cognitive learning theory
Διαθέσιμο Online:http://hdl.handle.net/10361/15759

Διαδίκτυο

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

Παρόμοια τεκμήρια