中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Deep Learning for Object Detection and Grasping: A Survey

文献类型:会议论文

作者Jia, Qun1,2; Jun, Cai3; Zhiqiang, Cao1,2; Yelan, Wu3; Xionglei, Zhao1,2; Junzhi, Yu1,2
出版日期2018-08
会议日期2018年8月11~13
会议地点武夷山
页码427-432
英文摘要

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.

会议录IEEE International Conference on Information and Automation
语种英语
源URL[http://ir.ia.ac.cn/handle/173211/23605]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队
通讯作者Zhiqiang, Cao
作者单位1.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
推荐引用方式
GB/T 7714
Jia, Qun,Jun, Cai,Zhiqiang, Cao,et al. Deep Learning for Object Detection and Grasping: A Survey[C]. 见:. 武夷山. 2018年8月11~13.

入库方式: OAI收割

来源:自动化研究所

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