CASIA OpenIR

浏览/检索结果: 共20条,第1-10条 帮助

限定条件                    
已选(0)清除 条数/页:   排序方式:
A Multi-Granularity Heterogeneous Graph for Extractive Text Summarization 期刊论文
ELECTRONICS, 2023, 卷号: 12, 期号: 10, 页码: 12
作者:  Zhao, Henghui;  Zhang, Wensheng;  Huang, Mengxing;  Feng, Siling;  Wu, Yuanyuan
收藏  |  浏览/下载:87/0  |  提交时间:2023/11/17
graph neural network  heterogeneous graph  attention mechanism  implicit topic  
Balance-Aware Grid Collage for Small Image Collections 期刊论文
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 2023, 卷号: 29, 期号: 2, 页码: 1330-1344
作者:  Song, Yu;  Tang, Fan;  Dong, Weiming;  Huang, Feiyue;  Lee, Tong-Yee;  Xu, Changsheng
收藏  |  浏览/下载:195/0  |  提交时间:2023/02/22
Grid collage  visual balance  reinforcement learning  
Intelligent contracts: Making smart contracts smart for blockchain intelligence 期刊论文
COMPUTERS & ELECTRICAL ENGINEERING, 2022, 卷号: 104, 页码: 15
作者:  Ouyang, Liwei;  Zhang, Wenwen;  Wang, Fei-Yue
Adobe PDF(1184Kb)  |  收藏  |  浏览/下载:217/42  |  提交时间:2023/02/22
Blockchain  Smart contracts  Blockchain intelligence  Decentralized artificial intelligence  
Collective Entity Alignment for Knowledge Fusion of Power Grid Dispatching Knowledge Graphs 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2021, 卷号: 9, 期号: 11, 页码: 1-15
作者:  Yang, Linyao;  Lv, Chen;  Wang, Xiao;  Qiao, Ji;  Ding, Weiping;  Zhang, Jun;  Wang, Fei-Yue
Adobe PDF(1600Kb)  |  收藏  |  浏览/下载:184/24  |  提交时间:2022/06/15
entity alignment  integer programming  knowledge fusion  knowledge graph embedding  power dispatch  
Picking out the Impurities: Attention-based Push-Grasping in Dense Clutter 期刊论文
ROBOTICA, 2022, 页码: 16
作者:  Lu, Ning;  Cai, Yinghao;  Lu, Tao;  Cao, Xiaoge;  Guo, Weiyan;  Wang, Shuo
收藏  |  浏览/下载:201/0  |  提交时间:2022/06/10
saliency Detection  robot Learning  push-grasp  target-oriented Grasping  deep Q Network  
Supervised assisted deep reinforcement learning for emergency voltage control of power systems 期刊论文
NEUROCOMPUTING, 2022, 卷号: 475, 页码: 69-79
作者:  Li, Xiaoshuang;  Wang, Xiao;  Zheng, Xinhu;  Dai, Yuxin;  Yu, Zhihong;  Zhang, Jun Jason;  Bu, Guangquan;  Wang, Fei-Yue
Adobe PDF(2551Kb)  |  收藏  |  浏览/下载:317/64  |  提交时间:2022/06/06
Deep reinforcement learning  Behavioral cloning  Dynamic demonstration  Emergency control  
HackGAN: Harmonious Cross-Network Mapping Using CycleGAN With Wasserstein-Procrustes Learning for Unsupervised Network Alignment 期刊论文
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS, 2022, 页码: 14
作者:  Yang, Linyao;  Wang, Xiao;  Zhang, Jun;  Yang, Jun;  Xu, Yancai;  Hou, Jiachen;  Xin, Kejun;  Wang, Fei-Yue
Adobe PDF(4053Kb)  |  收藏  |  浏览/下载:290/46  |  提交时间:2022/03/17
Task analysis  Optimization  Generative adversarial networks  Computational modeling  Automation  Training  Standards  Embedding  generative adversarial network  network alignment (NA)  optimal transport  unsupervised learning  
Progressive polarization based reflection removal via realistic training data generation 期刊论文
PATTERN RECOGNITION, 2022, 卷号: 124, 页码: 13
作者:  Pang, Youxin;  Yuan, Mengke;  Fu, Qiang;  Ren, Peiran;  Yan, Dong-Ming
Adobe PDF(4985Kb)  |  收藏  |  浏览/下载:306/39  |  提交时间:2022/02/16
Deep learning  Reflection removal  Polarization  Progressive network  Convolutional neural networks  
Meta-learning meets the Internet of Things: Graph prototypical models for sensor-based human activity recognition 期刊论文
INFORMATION FUSION, 2022, 卷号: 80, 页码: 1-22
作者:  Zheng, Wenbo;  Yan, Lan;  Gou, Chao;  Wang, Fei-Yue
收藏  |  浏览/下载:257/0  |  提交时间:2022/01/27
Meta-learning  Internet of Things  Graph model  Attention mechanisms  
Medical Term and Status Generation From Chinese Clinical Dialogue With Multi-Granularity Transformer 期刊论文
IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2021, 卷号: 29, 页码: 3362-3374
作者:  Li, Mei;  Xiang, Lu;  Kang, Xiaomian;  Zhao, Yang;  Zhou, Yu;  Zong, Chengqing
Adobe PDF(3036Kb)  |  收藏  |  浏览/下载:273/57  |  提交时间:2021/12/28
Medical diagnostic imaging  Transformers  Task analysis  Medical services  Computational modeling  Semantics  Data mining  Medical dialogue  multi-granularity  attention mechanism  natural language understanding  sequence to sequence learning