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A Cognitive Rail Track Breakage Detection System Using Artificial Neural Network Cover

A Cognitive Rail Track Breakage Detection System Using Artificial Neural Network

Applied Computer Systems
Volume 26 (2021): Issue 2 (December 2021)
By: ,  ,   and    
Open Access
|Dec 2021
Authors

Authors

Olufunke Rebecca Vincent

vincentor@funaab.edu.ng

Federal University of Agriculture, Abeokuta, Nigeria

Yetunde Ebunoluwa Babalola

Federal University of Agriculture, Abeokuta, Nigeria

Adesina Simon Sodiya

Federal University of Agriculture, Abeokuta, Nigeria

Olusola John Adeniran

Federal University of Agriculture, Abeokuta, Nigeria
DOI: https://doi.org/10.2478/acss-2021-0010 | Journal eISSN: 2255-8691 | Journal ISSN: 2255-8683
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Language: English
Page range: 80 - 86
Published on: Dec 30, 2021
Published by: Riga Technical University
In partnership with: Paradigm Publishing Services
Publication frequency: Volume open
Keywords:
Deep learning,
fully convolutional neural network,
rail track breakage,
U-Net architecture
Related subjects:
Computer sciences,
Artificial intelligence,
Information technology,
Project management,
Software development

© 2021 Olufunke Rebecca Vincent, Yetunde Ebunoluwa Babalola, Adesina Simon Sodiya, Olusola John Adeniran, published by Riga Technical University
This work is licensed under the Creative Commons Attribution 4.0 License.

Volume 26 (2021): Issue 2 (December 2021)
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