19IRTSTHN013), Doctor fund project of Zhengzhou University of Light Industry (No: 2014BSJJ016). 194200510016), Science and Technology Innovation Team Project of Henan Province University (No. ![]() This work is supported by the National Science Foundation of China under Grants (No: 61501407, 61603350, 61672471, 61873246), Key Science and Technology Program of Henan Province (202102210347, 202102210143), Key research project of Henan Province Universities (No: 19A413014), Plan For Scientific Innovation Talent of Henan Province (No: 184200510010), Center Plain Science and Technology Innovation Talents(No. Second, the visual saliency is introduced for micro-crack detection. First, an adaptive deep features extraction scheme without any supervised training is proposed for micro-crack detection.
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