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Weak Edge Identification Nets for Ocean Front Detection

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arxiv 1909.07827 v1 pith:BHFTGCI5 submitted 2019-09-17 cs.CV

Weak Edge Identification Nets for Ocean Front Detection

classification cs.CV
keywords frontoceandetectionedgegradientimageobtainoutput
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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The ocean front has an important impact in many areas, it is meaningful to obtain accurate ocean front positioning, therefore, ocean front detection is a very important task. However, the traditional edge detection algorithm does not detect the weak edge information of the ocean front very well. In response to this problem, we collected relevant ocean front gradient images and found relevant experts to calibrate the ocean front data to obtain groundtruth, and proposed a weak edge identification nets(WEIN) for ocean front detection. Whether it is qualitative or quantitative, our methods perform best. The method uses a welltrained deep learning model to accurately extract the ocean front from the ocean front gradient image. The detection network is divided into multiple stages, and the final output is a multi-stage output image fusion. The method uses the stochastic gradient descent and the correlation loss function to obtain a good ocean front image output.

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