The Algorithm Research of Image Classification Based on Deep Convolutional Network

被引：0
|
作者：
Wu DaQin [1 ]
Hu Haiyan [1 ]
机构：
[1] Jilin Business & Technol Coll, Dept Informat Engn, Changchun, Jilin, Peoples R China
来源：
2018 INTERNATIONAL CONFERENCE ON SMART GRID AND ELECTRICAL AUTOMATION (ICSGEA) | 2018年
关键词：
image convolution; deep learning; neural network; pattern recognition;
D O I：
10.1109/ICSGEA.2018.00064
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In order to solve large amount of images classification issues, a method is introduced by combining with Convolutional Neural Network(CNN) and IMVCI-10. Based on a large number of training data, the classification accuracy of the Convolution Neural Network can exceed the SVM classification accuracy. In this dataset, 3K and 100K batch data are used to train the depth convolution network, and the classification accuracy of 70% and more than 80% can be achieved.
引用
收藏
页码：231 / 233
页数：3
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