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

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A Cognitive Rail Track Breakage Detection System Using Artificial Neural Network

Applied Computer Systems

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

By: Olufunke Rebecca Vincent, Yetunde Ebunoluwa Babalola, Adesina Simon Sodiya and Olusola John Adeniran

Open Access

|Dec 2021

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:

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.

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