中文版 | English

在结果中检索

CASIA OpenIR
（本次检索基于用户作品认领结果）

浏览/检索结果: 共21条，第1-10条 帮助

限定条件            
已选(0)清除 条数/页：   排序方式：
Efficient Remote Sensing Image Super-Resolution via Lightweight Diffusion Models 期刊论文
IEEE Geoscience and Remote Sensing Letters, 2024, 卷号: 21, 页码: 1-5
作者:  An T(安泰);  Xue B(薛斌);  Huo CL(霍春雷);  Xiang SM(向世明);  Pan CH(潘春洪)
Adobe PDF(30422Kb)  |  收藏  |  浏览/下载：99/22  |  提交时间：2024/01/17
Remote sensing super-resolution  lightweight diffusion models  cross-attention mechanism  satellite imagery  
Graph convolutional network with tree-guided anisotropic message passing 期刊论文
NEURAL NETWORKS, 2023, 卷号: 165, 页码: 909-924
作者:  Wang, Ruixiang;  Wang, Yuhu;  Zhang, Chunxia;  Xiang, Shiming;  Pan, Chunhong
收藏  |  浏览/下载：36/0  |  提交时间：2023/11/17
Deep learning  Graph convolutional networks  Graph structure learning  Anisotropic message passing  
AutoMSNet: Multi-Source Spatio-Temporal Network via Automatic Neural Architecture Search for Traffic Flow Prediction 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 页码: 15
作者:  Fang, Shen;  Zhang, Chunxia;  Xiang, Shiming;  Pan, Chunhong
收藏  |  浏览/下载：134/0  |  提交时间：2023/02/22
Deep learning  neural architecture search  graph convolution  meta-learning  traffic flow prediction  
Subgraph-aware graph structure revision for spatial-temporal graph modeling 期刊论文
NEURAL NETWORKS, 2022, 卷号: 154, 页码: 190-202
作者:  Wang, Yuhu;  Zhang, Chunxia;  Xiang, Shiming;  Pan, Chunhong
收藏  |  浏览/下载：139/0  |  提交时间：2023/01/09
Graph structure learning  Graph neural network  Spatial-temporal graph modeling  
Task-aware adaptive attention learning for few-shot semantic segmentation 期刊论文
NEUROCOMPUTING, 2022, 卷号: 494, 页码: 104-115
作者:  Mao, Binjie;  Wang, Lingfeng;  Xiang, Shiming;  Pan, Chunhong
Adobe PDF(3903Kb)  |  收藏  |  浏览/下载：263/61  |  提交时间：2022/09/19
Few-shot semantic segmentation  Adaptive feature learning  Attention mechanism  Task-aware  
Learning adversarial point-wise domain alignment for stereo matching 期刊论文
NEUROCOMPUTING, 2022, 卷号: 491, 页码: 564-574
作者:  Zhang, Chenghao;  Meng, Gaofeng;  Xu, Richard Yi Da;  Xiang, Shiming;  Pan, Chunhong
Adobe PDF(3885Kb)  |  收藏  |  浏览/下载：253/49  |  提交时间：2022/09/19
Stereo Matching  Domain adaptation  Point-wise linear transformation  Adversarial learning  
Meta Graph Transformer: A Novel Framework for Spatial-Temporal Traffic Prediction 期刊论文
NEUROCOMPUTING, 2022, 卷号: 491, 页码: 544-563
作者:  Ye, Xue;  Fang, Shen;  Sun, Fang;  Zhang, Chunxia;  Xiang, Shiming
Adobe PDF(3491Kb)  |  收藏  |  浏览/下载：212/25  |  提交时间：2022/09/19
Traffic prediction  Spatial-temporal modeling  Meta-learning  Attention mechanism  Deep learning  
Monocular contextual constraint for stereo matching with adaptive weights assignment 期刊论文
IMAGE AND VISION COMPUTING, 2022, 卷号: 121, 页码: 10
作者:  Zhang, Chenghao;  Meng, Gaofeng;  Su, Bing;  Xiang, Shiming;  Pan, Chunhong
Adobe PDF(3669Kb)  |  收藏  |  浏览/下载：242/38  |  提交时间：2022/06/10
Deep learning  Stereo matching  Monocular contextual constraint  Adaptive weights assignment  
DATA: Differentiable ArchiTecture Approximation With Distribution Guided Sampling 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2021, 卷号: 43, 期号: 9, 页码: 2905-2920
作者:  Zhang, Xinbang;  Chang, Jianlong;  Guo, Yiwen;  Meng, Gaofeng;  Xiang, Shiming;  Lin, Zhouchen;  Pan, Chunhong
Adobe PDF(1346Kb)  |  收藏  |  浏览/下载：290/49  |  提交时间：2021/11/02
Computer architecture  Search problems  Optimization  Task analysis  Bridges  Binary codes  Estimation  Neural architecture search(NAS)  ensemble gumbel-softmax  distribution guided sampling  
You Only Search Once: Single Shot Neural Architecture Search via Direct Sparse Optimization 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2021, 卷号: 43, 期号: 9, 页码: 2891-2904
作者:  Zhang, Xinbang;  Huang, Zehao;  Wang, Naiyan;  Xiang, Shiming;  Pan, Chunhong
Adobe PDF(1271Kb)  |  收藏  |  浏览/下载：270/53  |  提交时间：2021/11/02
Computer architecture  Optimization  Learning (artificial intelligence)  Task analysis  Acceleration  Evolutionary computation  Convolution  Neural architecture search(NAS)  convolution neural network  sparse optimization