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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
会议名称IEEE International Conference on Information and Automation
会议录名称IEEE International Conference on Information and Automation
页码427-432
会议日期2018年8月11~13
会议地点武夷山
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.

语种英语
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/23605
专题复杂系统认知与决策实验室_先进机器人
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
第一作者单位中国科学院自动化研究所
通讯作者单位中国科学院自动化研究所
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],2018:427-432.
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