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Proceedings Paper

A meta-learning approach towards microvessel classification based on PAC-Bayes
Author(s): Juan Chen; Junchi Bao; Shiying Wang; Qian Yang
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Paper Abstract

In this work, we proposed a meta-learning method for the classification of microvessel images based on PAC-Bayes. We first introduce the modeling of Single-Opponent (SO) neurons to capture the color information of microvessel images. Then, we presented the PAC-Bayes bound on multiple learning tasks for the classification of microvessel images by optimizing the PAC-Bayes objective function. Further, we summarize the meta-learning algorithm based on PACBayes to classify microvessel images in detail. The proposed method is superior in precision and f1-score compared with other representative methods.

Paper Details

Date Published: 6 May 2019
PDF: 6 pages
Proc. SPIE 11069, Tenth International Conference on Graphics and Image Processing (ICGIP 2018), 110691G (6 May 2019); doi: 10.1117/12.2524363
Show Author Affiliations
Juan Chen, Univ. of Electronic Science and Technology of China (China)
Junchi Bao, Univ. of Electronic Science and Technology of China (China)
Shiying Wang, Univ. of Electronic Science and Technology of China (China)
Qian Yang, Univ. of Electronic Science and Technology of China (China)


Published in SPIE Proceedings Vol. 11069:
Tenth International Conference on Graphics and Image Processing (ICGIP 2018)
Chunming Li; Hui Yu; Zhigeng Pan; Yifei Pu, Editor(s)

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