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浏览/检索结果: 共7条，第1-7条 帮助 限定条件 发表日期：2021    内容类型：会议论文     已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 Active Pushing for Better Grasping in Dense Clutter with Deep Reinforcement Learning 会议论文 Shanghai, China, 6-8 Nov. 2020 作者:  Lu, Ning;  Lu, Tao;  Cai, Yinghao;  Wang, shuo 收藏  |  浏览/下载：8/0  |  提交时间：2021/06/01 Alignment control in off-Axis Gregorian system with reverse optimization method 会议论文 Beijing, China, 2021-06-20 作者:  Yin, Yamei;  Fu, Xing;  Lei, Yu;  Cao, Mingqiang 收藏  |  浏览/下载：26/0  |  提交时间：2022/01/30 Active optics  reverse optimization correction method  off-axis refractive system  wavefront aberration   Design of a catadioptric system for infrared star sensor with wide field of view 会议论文 Beijing, China, 2021-06-20 作者:  Yan, Haoyu;  Wang, Hu;  Xue, Yaoke;  Ma, Zehua 收藏  |  浏览/下载：51/0  |  提交时间：2022/01/30 Optical design  Infrared optical system  Star sensor  Catadioptric  Low air pressure  Wide spectrum   Super-resolution Imaging Lidar based on Fourier Ptychography 会议论文 Chengdu, China, 2021-06-14 作者:  Wang, Yuming;  Zhao, Hui;  Yang, Mingyang;  Qu, Youshan;  Fan, Xuewu 收藏  |  浏览/下载：29/0  |  提交时间：2022/03/10 Fourier ptychography  imaging lidar  phase retrieval  super-resolution   Design of hybrid refractive-diffractive star sensor optical system with wide field and small F-number 会议论文 Beijing, China, 2021-06-20 作者:  Ma, Zehua;  Wang, Hu;  Shen, Yang;  Xue, Yaoke;  Yan, Haoyu 收藏  |  浏览/下载：18/0  |  提交时间：2022/01/30 optical design  star sensor  hybrid refractive-diffractive  asphere  large field of view   A path planning strategy for marine vehicles based on deep reinforcement learning and data-driven dynamic flow fields prediction 会议论文 Dalian, China, July 15-17, 2021 作者:  Song SM(桑启明);  Tian Y(田宇);  Jin QL(金乾隆);  Yu JC(俞建成) 收藏  |  浏览/下载：6/0  |  提交时间：2021/11/21 marine vehicle  path planning  deep reinforcement learning  dynamic mode decomposition  sensing optimization   A deep learning model for joint prediction of three-dimensional ocean temperature, salinity and flow fields 会议论文 Dalian, China, July 15-17, 2021 作者:  Jin QL(金乾隆);  Tian Y(田宇);  Song SM(桑启明);  Liu SJ(刘世杰);  Yu JC(俞建成) 收藏  |  浏览/下载：6/0  |  提交时间：2021/11/21 ocean prediction  deep learning  convolutional LSTM  adaptive ocean sensing  marine vehicles