Design and Implementation of an Object Detection System Using Faster R-CNN

被引：9
|
作者：
Wang Cheng [1 ]
Peng Zhihao [2 ]
机构：
[1] Dalian Neusoft Univ Informat, Shool Digital Arts & Design, Dalian 116626, Peoples R China
[2] Dalian Neusoft Univ Informat, Shool Comp & Software, Dalian 116626, Peoples R China
来源：
2019 INTERNATIONAL CONFERENCE ON ROBOTS & INTELLIGENT SYSTEM (ICRIS 2019) | 2019年
关键词：
Regional proposal approach; Object detection; Convolutional Neural Network;
D O I：
10.1109/ICRIS.2019.00060
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Recent development in object detection are greatly driven by the success of region proposal approaches and region-based convolutional neural networks (R-CNNs). In this paper, we designed and implemented an object detection system using a faster-CNN method that shares full-image convolutional features with a detection network, so as to enable nearly cost-free region proposals. Development of this system is based on the previous work on Faster R-CNN. Results shows that with this method, we could achieve high accuracy while detecting objects.
引用
收藏
页码：204 / 206
页数：3
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