Integrated Learning System for Object Recognition from images based on Convolutional Neural Network

被引:0
|
作者
Jeong, Hyeok-june [1 ]
Lee, Myung-jae [1 ]
Ha, Young-guk [1 ]
机构
[1] Konkuk Univ, Dept Comp Sci & Engn, Seoul 143701, South Korea
来源
2016 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE & COMPUTATIONAL INTELLIGENCE (CSCI) | 2016年
关键词
deep learning; image recognition; Convolutional Neural Network; ontology; crawler;
D O I
10.1109/CSCI.2016.159
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
There has been an increase in the use of image processing for object recognition. However, traditional methods are not suitable in real-time system because they cannot satisfy human performance. Recently, deep learning with Convolutional Neural Network came to be known as a solution for image recognition. In fact, there are many great result with deep learning in object recognition. However, it needs a number of images to learn. In other words, it is necessary to manage images and categories. This paper proposes integrated object recognition system which manages and learns images. This system collects images automatically in classified categories and learns images in high accuracy. And multiple On-Board computer can share proposed learning system.
引用
收藏
页码:824 / 828
页数:5
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