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An Image Segmentation Based on a Piecewise Smooth Model in Deep Learning
- Choi, H.-T.;
- Derbel, B.;
- Hong, Byung-Woo
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0초록
We propose simple method that can solve the image segmentation problem in unsupervised manner. Our convolutional neural network is based on ResNet-18 to construct auto-encoder structure since the results with the ResNet-18 are reasonable. Our network optimizes the traditional segmentation algorithms: Chan-Vese algorithm and Mumford-Shah algorithm. Compared to some unsupervised segmentation algorithms that need additional modules to cover the inaccurate boundaries, our method can be trained end-to-end and consists of a simple objective function. © 2022 IEEE.
키워드
Chan-Vese algorithm; image segmentation; Mumford-shah algorithm; unsupervised learning
- 제목
- An Image Segmentation Based on a Piecewise Smooth Model in Deep Learning
- 저자
- Choi, H.-T.; Derbel, B.; Hong, Byung-Woo
- 발행일
- 2022-07
- 유형
- Proceedings Paper
- 저널명
- ITC-CSCC 2022 - 37th International Technical Conference on Circuits/Systems, Computers and Communications
- 페이지
- 294 ~ 297
- 언어
- ENG
- 출판사
- Institute of Electrical and Electronics Engineers Inc.
- 분량
- 4 페이지
- ISSN
- P 0000-0000