计算机工程2017，Vol.43Issue(6)：145-149,157,6.DOI:10.3969/j.issn.1000-3428.2017.06.024
分离多路卷积神经网络研究
Research on Detached Multiple Convolutional Neural Network
摘要
Abstract
As the Convolutional Neural Network(CNN) mainly uses the local features of the image,ignoring image channel features,this paper proposes a Detached Multiple Convolutional Neural Network (DMCNN).It extracts the channel features and convolution features,and fuses them in the whole connection layer so that image recognition and classification effects of the proposed network are improved.The experimental results on cifar10 and SVHN datasets show that the average recognition rate of the network is higher than that of other 8 CNNs like RexNet,Network in Network,Maxout.关键词
卷积神经网络/深度学习/特征提取/图像分类/图像识别/通道特征Key words
Convolutional Neural Network (CNN)/deep learning/feature extraction/image classification/image recognition/channel characteristic分类
信息技术与安全科学引用本文复制引用
宋超,许道云,秦永彬..分离多路卷积神经网络研究[J].计算机工程,2017,43(6):145-149,157,6.基金项目
国家自然科学基金(61262006,61540050) （61262006,61540050）
贵州省重大应用基础研究项目(黔科合JZ字[2014]2001) （黔科合JZ字[2014]2001）
贵州省科技厅联合基金(黔科合LH字[2014]7636号). （黔科合LH字[2014]7636号）
