Knowledge Commons of Institute of Automation,CAS
Deep Learning for Object Detection and Grasping: A Survey | |
Jia, Qun1,2![]() ![]() ![]() ![]() | |
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. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
0073.pdf(1373KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论