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., U-Net) for image segmentation purposes. The UGLS is made of three key ways, particularly, the coarse segmentation of concentrate on objects, era of boundary uncertainty maps for each object, and item wonderful segmentation. The coarse segmentation is used to detect potential object locations and exclude irrelevant track record considerably away from the detected locations. Together with the coarse segmentation, we will determine the locations in which object boundaries are likely to look and after that deliver boundary uncertainty maps for these objects, which often can largely greatly enhance the details about item boundaries and facilitate the boundary detection.
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We combine these uncertainty maps and unique enter pictures and feed them to the specified network for a more great segmentation. Following executing these a few actions, the network can attain a appreciably enhanced segmentation performance.
Especially, we implemented the fine segmentation of desirable objects utilizing the same configuration as their coarse segmentation (
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was made use of at the same time in morphological operations and Gaussian filter since it can make sure that pixels in the middle location of boundary uncertainty map have additional superior distinction or depth, as compared with the counterparts in other locations.
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