Integrated Learning System for Object Recognition from Images Based on Convolutional Neural Network
Hyeok-June Jeong, Myungjae Lee, Young-Guk Ha · 2016
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.