Design of classification system for cupping-induced plaque images based on deep learning

Yongjie Wang; Jianhua Qin

doi:10.1117/12.2671114

28 April 2023 Design of classification system for cupping-induced plaque images based on deep learning

Yongjie Wang, Jianhua Qin

Proceedings Volume 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022); 1261045 (2023) https://doi.org/10.1117/12.2671114
Event: Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 2022, Wuhan, China

Abstract

The purpose of this design is to improve the efficiency of cupping-induced plaque sorting and to meet the needs of the people to complete cupping-induced plaque sorting accurately. Deep learning methods and image classification techniques are used in the classification system to construct a classification model for cupping-induced plaques by migration learning on the RESNET convolutional neural network. The system classifies the cupping-induced plaque images based on that uploaded by the population. The experimental results shows that the classification accuracy of each category is above 80%, which verifies the effectiveness of the classification system.

Citation Download Citation

Yongjie Wang and Jianhua Qin "Design of classification system for cupping-induced plaque images based on deep learning", Proc. SPIE 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 1261045 (28 April 2023); https://doi.org/10.1117/12.2671114

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