CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 先进机器人
Deep Learning for Object Detection and Grasping: A Survey
Jia, Qun1,2; Jun, Cai3; Zhiqiang, Cao1,2; Yelan, Wu3; Xionglei, Zhao1,2; Junzhi, Yu1,2
2018-08
Conference NameIEEE International Conference on Information and Automation
Source PublicationIEEE International Conference on Information and Automation
Pages427-432
Conference Date2018年8月11~13
Conference Place武夷山
Abstract

Detecting and grasping objects in unstructured environments is an important yet difficult task. Fortunately, the breakthroughs from deep convolutional networks stimulate the development of object detection and grasping. The survey aims to serve as a comparison for region-based and region-free detection framework based on deep learning, and supplies the latest research results of object grasping with deep learning. Firstly, we briefly analyze the object detection and grasping. Then, the representative object detection methods based on deep learning are overviewed. Thirdly, we introduce the application of convolutional neural networks in object grasping. Finally, the potential trends in object detection and grasping based on deep learning are discussed.

Language英语
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/23605
Collection复杂系统管理与控制国家重点实验室_先进机器人
Corresponding AuthorZhiqiang, Cao
Affiliation1.The state key laboratory of management and control for complex systems, Institute of Automation, Chinese Academy of Sciences
2.University of Chinese Academy of Sciences
3.School of Computer & Information Engineering, Beijing Technology and Business University
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Jia, Qun,Jun, Cai,Zhiqiang, Cao,et al. Deep Learning for Object Detection and Grasping: A Survey[C],2018:427-432.
Files in This Item: Download All
File Name/Size DocType Version Access License
0073.pdf(1373KB)会议论文 开放获取CC BY-NC-SAView Download
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Jia, Qun]'s Articles
[Jun, Cai]'s Articles
[Zhiqiang, Cao]'s Articles
Baidu academic
Similar articles in Baidu academic
[Jia, Qun]'s Articles
[Jun, Cai]'s Articles
[Zhiqiang, Cao]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Jia, Qun]'s Articles
[Jun, Cai]'s Articles
[Zhiqiang, Cao]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: 0073.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.