Unsupervised saliency detection of rail surface defects using stereoscopic images

Visual information is increasingly recognized as a useful method to detect rail surface defects due to its high efficiency and stability. However, it cannot sufficiently detect a complete defect in the complex background information. The addition of surface profiles can effectively improve this by i...

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Bibliographic Details

Main Authors:	Menghui Niu, Kechen Song, Liming Huang, Qi Wang, Yunhui Yan, Qinggang Meng
Format:	Default Article
Published:	2020
Subjects:	line-scanning system low-rank nonnegative reconstruction rail defects detection saliency stereoscopic
Online Access:	https://hdl.handle.net/2134/13337936.v1
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