CASIA OpenIR

浏览/检索结果: 共7条,第1-7条 帮助

限定条件    
已选(0)清除 条数/页:   排序方式:
Second-Order Global Attention Networks for Graph Classification and Regression 会议论文
, Beijing, China, August 27-28, 2022
作者:  Hu Fenyu;  Cui Zeyu;  Wu Shu;  Liu Qiang;  Wu Jinlin;  Wang Liang;  Tan Tieniu
Adobe PDF(69424Kb)  |  收藏  |  浏览/下载:178/67  |  提交时间:2023/07/06
基于脑网络组图谱的精神分裂症亚型研究 学位论文
, 2022
作者:  时维阳
Adobe PDF(46558Kb)  |  收藏  |  浏览/下载:225/9  |  提交时间:2022/12/22
精神分裂症  异质性  亚型  影像-临床关联分析  影像-转录组关联分析  
Driving EEG based multilayer dynamic brain network analysis for steering process 期刊论文
EXPERT SYSTEMS WITH APPLICATIONS, 2022, 卷号: 207, 页码: 17
作者:  Chang, Wenwen;  Meng, Weiliang;  Yan, Guanghui;  Zhang, Bingtao;  Luo, Hao;  Gao, Rui;  Yang, Zhifei
Adobe PDF(13070Kb)  |  收藏  |  浏览/下载:340/81  |  提交时间:2022/09/19
Multi -layer Networks  Functional Connectivity  Electroencephalogram (EEG)  Driving Intention  Feature Extraction  Driving Behavior  
Disaster Prediction Knowledge Graph Based on Multi-Source Spatio-Temporal Information 期刊论文
Remote Sensing, 2022, 期号: 14, 页码: 1214
作者:  Ge, Xingtong;  Yang, Yi;  Chen, Jiahui;  Li, Weichao;  Huang, Zhisheng;  Zhang, Wenyue;  Peng, Ling
Adobe PDF(7193Kb)  |  收藏  |  浏览/下载:237/50  |  提交时间:2022/03/31
disaster prediction knowledge graph  spatio-temporal  disaster dynamic prediction  multi-source data fusion  forest fire risk prediction  geological landslide risk prediction  
Boost 3-D Object Detection via Point Clouds Segmentation and Fused 3-D GIoU-L-1 Loss 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 卷号: 33, 期号: 2, 页码: 762-773
作者:  Chen, Yaran;  Li, Haoran;  Gao, Ruiyuan;  Zhao, Dongbin
Adobe PDF(2082Kb)  |  收藏  |  浏览/下载:232/48  |  提交时间:2022/03/17
3-D object detection  generalized Intersection of Union (GIoU) loss  segmentation  
An Adaptive Rapidly-Exploring Random Tree 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2022, 卷号: 9, 期号: 2, 页码: 283-294
作者:  Binghui Li;  Badong Chen
Adobe PDF(2449Kb)  |  收藏  |  浏览/下载:144/32  |  提交时间:2021/11/03
Narrow passage  path planning  rapidly-exploring random tree (RRT)-Connect  sampling-based algorithm  
Sampling Methods for Efficient Training of Graph Convolutional Networks: A Survey 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2022, 卷号: 9, 期号: 2, 页码: 205-234
作者:  Xin Liu;  Mingyu Yan;  Lei Deng;  Guoqi Li;  Xiaochun Ye;  Dongrui Fan
Adobe PDF(2300Kb)  |  收藏  |  浏览/下载:216/39  |  提交时间:2021/11/03
Efficient training  graph convolutional networks (GCNs)  graph neural networks (GNNs)  sampling method