RPN-FCN based rust detection on power equipment

Yuan, Jiangru; Xue, Bing; Zhang, Weishan; Xu, Liang; Sun, Haoyun; Zhou, Jiehan (2019-02-06)
 
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URL:
https://doi.org/10.1016/j.procs.2019.01.236

Yuan, Jiangru
Xue, Bing
Zhang, Weishan
Xu, Liang
Sun, Haoyun
Zhou, Jiehan
Elsevier
06.02.2019

Jiangru Yuan, Bing Xue, Weishan Zhang, Liang Xu, Haoyun Sun, Jiehan Zhou, RPN-FCN based Rust detection on power equipment, Procedia Computer Science, Volume 147, 2019, Pages 349-353, ISSN 1877-0509, https://doi.org/10.1016/j.procs.2019.01.236

https://creativecommons.org/licenses/by-nc-nd/4.0/
© 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/).
https://creativecommons.org/licenses/by-nc-nd/4.0/
doi:https://doi.org/10.1016/j.procs.2019.01.236
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2019101032129
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Abstract

This paper proposes a novel RPN-FCN based rust detection approach. The RPN-FCN generates region proposals with RPN and performs full convolution for semantic segmentation of rust. The experimental result demonstrate that this approach improves the accuracy of rust detection compared with other neural networks.

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https://creativecommons.org/licenses/by-nc-nd/4.0/
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