ML-DSVM+: A meta-learning based deep SVM+ for computer-aided diagnosis

作者：

Highlights：

• A novel meta-learning based deep neural network SVM+ (ML-DSVM+) algorithm is proposed for CAD

• ML-DSVM+ integrates the bi-channel DNNs and SVM+ into a unified framework for optimization

• A new coupled hinge loss is proposed to perform supervised bidirectional transfer

• ML-DSVM+ can effectively alleviate the issues of class imbalance and overfitting

摘要

•A novel meta-learning based deep neural network SVM+ (ML-DSVM+) algorithm is proposed for CAD•ML-DSVM+ integrates the bi-channel DNNs and SVM+ into a unified framework for optimization•A new coupled hinge loss is proposed to perform supervised bidirectional transfer•ML-DSVM+ can effectively alleviate the issues of class imbalance and overfitting

论文关键词：Deep neural network,Support vector machine plus,Learning using privileged information,Meta-learning

论文评审过程：Received 23 March 2021, Revised 10 June 2022, Accepted 25 September 2022, Available online 27 September 2022, Version of Record 30 September 2022.

论文官网地址：https://doi.org/10.1016/j.patcog.2022.109076