Mingming Yang,Tinghuai Ma,Qing Tian,Yuan Tian,Abdullah Al-Dhelaan,Mohammed Al-Dhelaan.Aggregated squeeze-and-excitation transformations for densely connected convolutional networks[J].The Visual Computer,2021.

Zhang Xiangyu,Li Jianqing,Cai Zhipeng,Zhang Li,Chen Zhenghua,Liu Chengyu.Over-fitting suppression training strategies for deep learning-based atrial fibrillation detection.[J].Medical & biological engineering & computing,2021.

Wang Haojun,Long Haixia,Wang Ailan,Liu Tianyue,Fu Haiyan.Deep Learning and Regularization Algorithms for Malicious Code Classification[J].IEEE ACCESS,2021.

Marin Ivana,Skelin Ana Kuzmanic,Grujic Tamara.Empirical Evaluation of the Effect of Optimization and Regularization Techniques on the Generalization Performance of Deep Convolutional Neural Network[J].APPLIED SCIENCES-BASEL,2020.

Hengyue Pan,Xin Niu,Rongchun Li,Siqi Shen,Yong Dou.DropFilterR: A Novel Regularization Method for Learning Convolutional Neural Networks[J].Neural Processing Letters,2019.

Nitish Srivastava,Geoffrey E. Hinton,Alex Krizhevsky,Ilya Sutskever,Ruslan Salakhutdinov.Dropout: a simple way to prevent neural networks from overfitting.[J].Journal of Machine Learning Research,2014.

谢璐阳,夏兆君,朱少华,张代庆,赵奉奎.基于卷积神经网络的图像识别过拟合问题分析与研究[J].软件工程,2019(10).

任义丽,罗路.卷积神经网络过拟合问题研究[J].信息系统工程,2019(05).

宋长明,王赟.融合低秩和稀疏表示的图像超分辨率重建算法[J].西安交通大学学报,2018(07).

吕永标,赵建伟,曹飞龙.基于复合卷积神经网络的图像去噪算法[J].模式识别与人工智能,2017(02).