中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
机构
  • 沈阳自动化研究所 [23]
采集方式
内容类型
发表日期
学科主题
筛选

浏览/检索结果: 共23条,第1-10条 帮助

限定条件                
条数/页: 排序方式:
Towards collaborative appearance and semantic adaptation for medical image segmentation 期刊论文  OAI收割
Neurocomputing, 2022, 页码: 1-11
作者:  
Wang Q(王强);  Du YK(杜英魁);  Fan HJ(范慧杰);  Ma, Chi
  |  收藏  |  
Adaptive learning attention network for underwater image enhancement 期刊论文  OAI收割
IEEE Robotics and Automation Letters, 2022, 卷号: 7, 期号: 2, 页码: 5326-5333
作者:  
Liu SB(刘世本);  Fan HJ(范慧杰);  Lin S(林森);  Wang Q(王强);  Ding ND(丁乃达)
  |  收藏  |  
基于深度学习的颅内肿瘤辅助分析方法研究 学位论文  OAI收割
沈阳: 中国科学院沈阳自动化研究所, 2021
作者:  
黄钲
  |  收藏  |  
Intelligent Scheduling for Permutation Flow Shop with Dynamic Job Arrival via Deep Reinforcement Learning 会议论文  OAI收割
Chongqing, China, March 12-14, 2021
作者:  
Yang SL(杨圣落);  Xu ZG(徐志刚)
  |  收藏  |  
Research on Intelligent Protection Technology for Distribution Network with Distributed Generation 会议论文  OAI收割
Chongqing, China, March 12-14, 2021
作者:  
Cui SJ(崔世界);  Zeng P(曾鹏);  Wang ZF(王忠锋);  Song CH(宋纯贺)
  |  收藏  |  
Efficient federated learning for fault diagnosis in industrial cloud-edge computing 期刊论文  OAI收割
Computing, 2021, 卷号: 103, 期号: 10, 页码: 2319-2337
作者:  
Wang QZ(王其朝);  Li Q(李庆);  Wang K(王锴);  Wang H(王宏);  Zeng P(曾鹏)
  |  收藏  |  
Abnormal Traffic Detection of Industrial Edge Network Based on Deep Nature Learning 会议论文  OAI收割
Dublin, Ireland, July 19-23, 2021
作者:  
Liu Q(刘琦);  Zhang BW(张博文);  Zhao JM(赵剑明);  Zang CZ(臧传治);  Wang, Xibo
  |  收藏  |  
A Fast and Energy-Saving Neural Network Inference Method for Fault Diagnosis of Industrial Equipment Based on Edge-End Collaboration 会议论文  OAI收割
Jiaxing, China, July 27-31, 2021
作者:  
Wang QZ(王其朝);  Jin GS(金光淑);  Li Q(李庆);  Wang K(王锴);  Yang ZY(杨祖业)
  |  收藏  |  
Path planning of mobile robot based on improved DDQN 会议论文  OAI收割
Changsha, Virtual, China, August 20-22, 2021
作者:  
Yang, Yunxiao;  Wang, Jun;  Zhang HL(张华良);  Dai, Shilong
  |  收藏  |  
A path planning strategy for marine vehicles based on deep reinforcement learning and data-driven dynamic flow fields prediction 会议论文  OAI收割
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  |