Research on image classification model based on deep convolution neural network

EURASIP Journal on Image and Video Processing

Yong Wang¹  Mingyuan Xin² 

[1] Heihe University;School of Computer and Information Engineering, Heihe University;

关键词: Convolution neural network;    Image classification;    M3CE-CEc;   

DOI  :  10.1186/s13640-019-0417-8

来源: DOAJ

【 摘 要 】

Abstract Based on the analysis of the error backpropagation algorithm, we propose an innovative training criterion of depth neural network for maximum interval minimum classification error. At the same time, the cross entropy and M3CE are analyzed and combined to obtain better results. Finally, we tested our proposed M3 CE-CEc on two deep learning standard databases, MNIST and CIFAR-10. The experimental results show that M3 CE can enhance the cross-entropy, and it is an effective supplement to the cross-entropy criterion. M3 CE-CEc has obtained good results in both databases.

【 授权许可】

Unknown