CASIA OpenIR
(本次检索基于用户作品认领结果)

浏览/检索结果: 共27条,第1-10条 帮助

限定条件                
已选(0)清除 条数/页:   排序方式:
GFFNet: Global Feature Fusion Network for Semantic Segmentation of Large-Scale Remote Sensing Images 期刊论文
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2024, 卷号: 17, 期号: 2024, 页码: 4222 - 4234
作者:  Cao, Yong;  Huo, Chunlei;  Xiang, Shiming;  Pan, Chunhong
Adobe PDF(4340Kb)  |  收藏  |  浏览/下载:7/2  |  提交时间:2024/06/25
Cross feature fusion (CFF)  global context learning  group transformer  semantic segmentation  
Patch Loss: A generic multi-scale perceptual loss for single image super-resolution 期刊论文
Pattern Recognition, 2023, 卷号: 139, 页码: 109510
作者:  An T(安泰);  Mao BJ(毛彬杰);  Xue B(薛斌);  Huo CL(霍春雷);  Xiang SM(向世明);  Pan CH(潘春洪)
Adobe PDF(5876Kb)  |  收藏  |  浏览/下载:128/20  |  提交时间:2024/01/17
Single-image super-resolution  Multi-scale loss functions  Image visual perception  Perceptual metrics  
Combining discrete and continuous representation: Scale-arbitrary super-resolution for satellite images 期刊论文
Remote Sensing, 2023, 卷号: 15, 页码: 1827
作者:  An T(安泰);  Huo CL(霍春雷);  Xiang SM(向世明);  Pan CH(潘春洪)
Adobe PDF(14935Kb)  |  收藏  |  浏览/下载:95/13  |  提交时间:2024/01/17
scale-arbitrary super-resolution  image representation  satellite imagery  
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:313/72  |  提交时间:2022/09/19
Few-shot semantic segmentation  Adaptive feature learning  Attention mechanism  Task-aware  
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:284/44  |  提交时间:2022/06/10
Deep learning  Stereo matching  Monocular contextual constraint  Adaptive weights assignment  
HENet: Head-Level Ensemble Network for Very High Resolution Remote Sensing Images Semantic Segmentation 期刊论文
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2022, 卷号: 19, 页码: 5
作者:  Cao, Yong;  Huo, Chunlei;  Xu, Nuo;  Zhang, Xin;  Xiang, Shiming;  Pan, Chunhong
Adobe PDF(1478Kb)  |  收藏  |  浏览/下载:262/4  |  提交时间:2022/06/06
Head  Computational modeling  Semantics  Image segmentation  Feature extraction  Correlation  Mathematical models  Cooperative learning (CL)  ensemble learning  semantic segmentation  
CMT: Cross Mean Teacher Unsupervised Domain Adaptation for VHR Image Semantic Segmentation 期刊论文
IEEE Geoscience and Remote Sensing Letters, 2021, 卷号: 0, 期号: 0, 页码: 1-5
作者:  Liang Yan;  Bin Fan;  Shiming Xiang;  Chunhong Pan
Adobe PDF(1700Kb)  |  收藏  |  浏览/下载:192/41  |  提交时间:2021/06/15
Cross mean teacher (CMT)  self-training (ST)  semantic segmentation  unsupervised domain adaptation (UDA)  very-high-resolution (VHR) image  
3D PostureNet: A unified framework for skeleton-based posture recognition 期刊论文
PATTERN RECOGNITION LETTERS, 2020, 卷号: 140, 期号: 140, 页码: 143-149
作者:  Liu, Jianbo;  Wang, Ying;  Liu, Yongcheng;  Xiang, Shiming;  Pan, Chunhong
Adobe PDF(1997Kb)  |  收藏  |  浏览/下载:288/41  |  提交时间:2021/03/02
Human posture recognition  Static hand gesture recognition  Skeleton-based  3D convolutional neural network  
Triplet Adversarial Domain Adaptation for Pixel-Level Classification of VHR Remote Sensing Images 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2020, 卷号: 58, 期号: 5, 页码: 3558-3573
作者:  Yan, Liang;  Fan, Bin;  Liu, Hongmin;  Huo, Chunlei;  Xiang, Shiming;  Pan, Chunhong
Adobe PDF(6348Kb)  |  收藏  |  浏览/下载:390/83  |  提交时间:2020/06/22
Domain adaptation (DA)  pixel-level classification  self-training  triplet adversarial learning  very high resolution (VHR)  
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:482/111  |  提交时间:2019/12/16
Deep learning  Graph convolutional neural networks  Graph structure learning  Changeable kernel sizes