CASIA OpenIR
(本次检索基于用户作品认领结果)

浏览/检索结果: 共6条,第1-6条 帮助

限定条件            
已选(0)清除 条数/页:   排序方式:
MS-Net: Multi-Source Spatio-Temporal Network for Traffic Flow Prediction 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2021, 卷号: 23, 期号: 7, 页码: 14
作者:  Fang, Shen;  Prinet, Veronique;  Chang, Jianlong;  Werman, Michael;  Zhang, Chunxia;  Xiang, Shiming;  Pan, Chunhong
收藏  |  浏览/下载:222/0  |  提交时间:2022/01/27
Feature extraction  Convolution  Predictive models  Data models  Correlation  Roads  Kernel  Graph convolution  deep attention mechanism  traffic network  traffic flow prediction  artificial intelligence  deep learning  
Spatio-Temporal Graph Structure Learning for Traffic Forecasting 会议论文
, New York, USA, 2020-02
作者:  Zhang Qi;  Chang Jianlong;  Meng Gaofeng;  Xiang Shiming;  Pan Chunhong
Adobe PDF(541Kb)  |  收藏  |  浏览/下载:204/43  |  提交时间:2021/05/31
Kernel-Weighted Graph Convolutional Network: A Deep Learning Approach for Traffic Forecasting 会议论文
, Beijing, China, 2018-08
作者:  Zhang Qi;  Jin Qizhao;  Chang Jianlong;  Xiang Shiming;  Pan Chunhong
Adobe PDF(4041Kb)  |  收藏  |  浏览/下载:176/32  |  提交时间:2021/05/31
Local-Aggregation Graph Networks 期刊论文
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020, 卷号: 42, 期号: 11, 页码: 2874-2886
作者:  Jianlong Chang;  Lingfeng Wang;  Gaofeng Meng;  Shiming Xiang;  Chunhong Pan
浏览  |  Adobe PDF(3090Kb)  |  收藏  |  浏览/下载:251/90  |  提交时间:2020/10/20
Local-aggregation function  local-aggregation graph neural network  non-Euclidean structured signal  
Structure-Aware Convolutional Neural Networks 会议论文
, 加拿大, 2018.12
作者:  Chang, Jianlong
Adobe PDF(1401Kb)  |  收藏  |  浏览/下载:305/97  |  提交时间:2020/06/10
Structure-Aware Convolution  
Learning graph structure via graph convolutional networks 期刊论文
PATTERN RECOGNITION, 2019, 卷号: 95, 期号: -, 页码: 308-318
作者:  Zhang, Qi;  Chang, Jianlong;  Meng, Gaofeng;  Xu, Shibiao;  Xiang, Shiming;  Pan, Chunhong
浏览  |  Adobe PDF(2475Kb)  |  收藏  |  浏览/下载:454/107  |  提交时间:2019/12/16
Deep learning  Graph convolutional neural networks  Graph structure learning  Changeable kernel sizes