FHENet: lightweight feature hierarchical exploration network for real-time rail surface defect inspection in RGB-D images

In recent years, computer vision systems have been increasingly applied to rail defect inspection. Rail defects should be identified quickly and accurately to ensure safe, stable, and fast train operations and thereby reduce the incidence of accidents and economic losses. As most existing methods fo...

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Main Authors: Zhou, Wujie, Hong, Jiankang
其他作者: School of Computer Science and Engineering
格式: Article
語言:English
出版: 2023
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在線閱讀:https://hdl.handle.net/10356/170750
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