A meta-learning approach towards microvessel classification based on PAC-Bayes

Juan Chen; Junchi Bao; Shiying Wang; Qian Yang

doi:10.1117/12.2524363

6 May 2019 A meta-learning approach towards microvessel classification based on PAC-Bayes

Juan Chen, Junchi Bao, Shiying Wang, Qian Yang

Proceedings Volume 11069, Tenth International Conference on Graphics and Image Processing (ICGIP 2018); 110691G (2019) https://doi.org/10.1117/12.2524363
Event: Tenth International Conference on Graphic and Image Processing (ICGIP 2018), 2018, Chengdu, China

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.

Citation Download Citation

Juan Chen, Junchi Bao, Shiying Wang, and Qian Yang "A meta-learning approach towards microvessel classification based on PAC-Bayes", Proc. SPIE 11069, Tenth International Conference on Graphics and Image Processing (ICGIP 2018), 110691G (6 May 2019); https://doi.org/10.1117/12.2524363

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