Evolving semantic object segmentation methods automatically by genetic programming from images and image processing operators-Reference-Cited by-同舟云学术

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Evolving semantic object segmentation methods automatically by genetic programming from images and image processing operators

Published:2020-02-13 Issue:17 Volume:24 Page:12887-12900
ISSN:1432-7643
Container-title:Soft Computing
language:en
Short-container-title:Soft Comput

Author:

Liang Jiayu,Wen Jixiang,Wang Zhe,Wang Jianming

Funder

National Natural Science Foundation of China

Tianjin Science and Technology Program

Publisher

Springer Science and Business Media LLC

Subject

Geometry and Topology,Theoretical Computer Science,Software

Link

http://link.springer.com/content/pdf/10.1007/s00500-020-04713-1.pdf

Reference31 articles.

1. Active contour based segmentation. http://au.mathworks.com/help/images/ref/activecont-our.htmlbtuep4x-7

2. Thresholding segmentation. http://au.mathworks.com/help/images/examples/correcting-nonuniform-illumination.html

3. Banzhaf W, Nordin P, Keller RE, Francone FD (1998) Genetic programming: an introduction. Morgan Kaufmann Publishers, San Francisco

4. Borenstein E, Ullman S (2008) Combined top-down/bottom-up segmentation. IEEE Trans Pattern Anal Mach Intell 30(12):2109–2125

5. Dong M, Eramian MG, Ludwig SA, Pierson RA (2013) Automatic detection and segmentation of bovine corpora lutea in ultrasonographic ovarian images using genetic programming and rotation invariant local binary patterns. Med Biol Eng Comput 51(4):405–416

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