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CASIA OpenIR
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Continual Stereo Matching of Continuous Driving Scenes with Growing Architecture 会议论文
, 美国路易斯安那州新奥尔良, 2022.06.19
作者:  Zhang, Chenghao;  Tian, Kun;  Fan, Bin;  Meng, Gaofeng;  Zhang, Zhaoxiang;  Pan, Chunhong
Adobe PDF(2647Kb)  |  收藏  |  浏览/下载：155/56  |  提交时间：2023/04/25
Multi-modal spatio-temporal meteorological forecasting with deep neural network 期刊论文
ISPRS Journal of Photogrammetry and Remote Sensing, 2022, 页码: 14
作者:  Xinbang Zhang;  Qizhao Jin;  Tingzhao Yu;  Shiming Xiang;  Qiuming Kuang;  Véronique Prinet;  Chunhong Pan
Adobe PDF(3735Kb)  |  收藏  |  浏览/下载：285/68  |  提交时间：2022/07/01
Meterological forecasting  Deep learning  Neural architecture search  AutoML  
AME: Attention and Memory Enhancement in Hyper-Parameter Optimization 会议论文
, New Orleans, USA, 2022.6.19-6.24
作者:  Xu, Nuo;  Chang, Jianlong;  Nie, Xing;  Huo, Chunlei;  Xiang, Shiming;  Pan, Chunhong
Adobe PDF(913Kb)  |  收藏  |  浏览/下载：168/40  |  提交时间：2022/12/20
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：292/49  |  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：272/53  |  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  
Decoupled Representation Learning for Character Glyph Synthesis 期刊论文
IEEE Transactions on Multimedia, 2021, 卷号: 2021, 期号: 2021, 页码: 1-13
作者:  Xiyan Liu;  Gaofeng Meng;  Jianlong Chang;  Ruiguang Hu;  Shiming Xiang;  Chunhong Pan
Adobe PDF(4588Kb)  |  收藏  |  浏览/下载：176/46  |  提交时间：2022/01/24
Character glyph synthesis  Decoupled representation  generative adversarial networks  
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：151/31  |  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  
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：336/61  |  提交时间：2020/06/22
Domain adaptation (DA)  pixel-level classification  self-training  triplet adversarial learning  very high resolution (VHR)  
Deep Self-Evolution Clustering 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2020, 卷号: 42, 期号: 4, 页码: 809-823
作者:  Chang, Jianlong;  Meng, Gaofeng;  Wang, Lingfeng;  Xiang, Shiming;  Pan, Chunhong
浏览  |  Adobe PDF(4817Kb)  |  收藏  |  浏览/下载：394/86  |  提交时间：2020/06/02
Task analysis  Unsupervised learning  Training  Clustering methods  Pattern analysis  Clustering  deep self-evolution clustering  self-evolution clustering training  deep unsupervised learning  
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：437/102  |  提交时间：2019/12/16
Deep learning  Graph convolutional neural networks  Graph structure learning  Changeable kernel sizes