Multi-stage feature decorrelation constraints for improving CNN classification performance

1 code implementation • 24 Aug 2023 • Qiuyu Zhu, Hao Wang, Xuewen Zu, Chengfei Liu

Considering that there are many layers in CNN, through experimental comparison and analysis, MFD Loss acts on multiple front layers of CNN, constrains the output features of each layer and each channel, and performs supervision training jointly with classification loss function during network training.

A Softmax-free Loss Function Based on Predefined Optimal-distribution of Latent Features for Deep Learning Classifier

1 code implementation • 25 Nov 2021 • Qiuyu Zhu, Xuewen Zu

The loss function only restricts the latent features of the samples, including the norm-adaptive Cosine distance between the latent feature vector of the sample and the center of the predefined evenly-distributed class, and the correlation between the latent features of the samples.

Classification