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ThreshNet: Segmentation Refinement Inspired by Region-Specific Thresholding. (arXiv:2211.06560v1 [cs.CV])
Nov. 15, 2022, 2:15 a.m. | Savinay Nagendra, Chaopeng Shen, Daniel Kifer
cs.CV updates on arXiv.org arxiv.org
We present ThreshNet, a post-processing method to refine the output of neural
networks designed for binary segmentation tasks. ThreshNet uses the confidence
map produced by a base network along with global and local patch information to
significantly improve the performance of even state-of-the-art methods. Binary
segmentation models typically convert confidence maps into predictions by
thresholding the confidence scores at 0.5 (or some other fixed number).
However, we observe that the best threshold is image-dependent and often even
region-specific -- different …
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