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浏览/检索结果: 共4条，第1-4条 帮助 限定条件 专题：长春光学精密机械与物理研究所    第一署名单位    第一作者单位    通讯作者单位     已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择发表日期升序发表日期降序提交时间升序提交时间降序题名升序题名降序作者升序作者降序 KDA3D: Key-Point Densification and Multi-Attention Guidance for 3D Object Detection 期刊论文 Remote Sensing, 2020, 卷号: 12, 期号: 11, 页码: 27 作者:  J. R. Wang,M. Zhu,B. Wang,D. Y. Sun,H. Wei,C. J. Liu and H. T. Nie 收藏  |  浏览/下载：2/0  |  提交时间：2021/07/06 Three-dimentional reconstruction of semantic scene based on RGB-D map 期刊论文 Guangxue Jingmi Gongcheng/Optics and Precision Engineering, 2018, 卷号: 26, 期号: 5, 页码: 1231-1241 作者:  Lin, Jin-Hua;  Wang, Yan-Jie 收藏  |  浏览/下载：6/0  |  提交时间：2019/09/17 Image reconstruction  Computer system recovery  Computer vision  Convolution  Learning systems  Machinery  Restoration  Semantics  Three dimensional computer graphics   Object recognition based on shape feature fusion under multi-views 期刊论文 Guangxue Jingmi Gongcheng/Optics and Precision Engineering, 2014, 卷号: 22, 期号: 12, 页码: 3368-3376 Li P.; Wei Z.-H.; He X.; He D.-L.; He J.-W.; Liang G.-L.; Ling J.-Y. 收藏  |  浏览/下载：22/0  |  提交时间：2015/04/24 Research on station mode for attitude determination of multiple targets (EI CONFERENCE) 会议论文 2010 International Conference on Computational and Information Sciences, ICCIS2010, December 17, 2010 - December 19, 2010, Chengdu, Sichuan, China Li M.; Wang J.; Zhao L. 收藏  |  浏览/下载：27/0  |  提交时间：2013/03/25 A key problem of attitude determination system is how to locate CMOS cameras and deal with relations among them. In this paper  several kinds of multi-CMOS station mode are introduced. Fundamental principles and classification of station mode directly affect on measurement parameters of system. No matter what mode is designed  the ultimate goal is to extend Effective Viewing Field (EVF)  increase capture ratio of objects and increase measurement precision. Station mode introduced in this paper is made of CMOS cameras  because of low cost  high speed frame frequency and low power consumption  CMOS cameras were putted near from object tested. So sequences of image are legible  which are convenient for analysis of three dimensional(3D) attitude. 2010 IEEE.