Rethinking Automatic Ship Wake Detection: State-of-the-Art CNN-based Wake Detection via Optical Images

Author(s):  
Fuduo Xue ◽  
Weiqi Jin ◽  
Su Qiu ◽  
Jie Yang
2021 ◽  
Vol 258 ◽  
pp. 112375
Author(s):  
Yingfei Liu ◽  
Jun Zhao ◽  
Yan Qin

2020 ◽  
Vol 58 (3) ◽  
pp. 1665-1677 ◽  
Author(s):  
Oktay Karakus ◽  
Igor Rizaev ◽  
Alin Achim

2018 ◽  
Vol 15 (7) ◽  
pp. 1055-1059 ◽  
Author(s):  
Zhou Xu ◽  
Bo Tang ◽  
Shuiying Cheng
Keyword(s):  

2011 ◽  
Vol 2011 ◽  
pp. 1-20 ◽  
Author(s):  
Sylvie Chambon ◽  
Jean-Marc Moliard

In the field of noninvasive sensing techniques for civil infrastructures monitoring, this paper addresses the problem of crack detection, in the surface of the French national roads, by automatic analysis of optical images. The first contribution is a state of the art of the image-processing tools applied to civil engineering. The second contribution is about fine-defect detection in pavement surface. The approach is based on a multi-scale extraction and a Markovian segmentation. Third, an evaluation and comparison protocol which has been designed for evaluating this difficult task—the road pavement crack detection—is introduced. Finally, the proposed method is validated, analysed, and compared to a detection approach based on morphological tools.


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