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CASIA OpenIR
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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：296/70  |  提交时间：2022/07/01
Meterological forecasting  Deep learning  Neural architecture search  AutoML  
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：183/48  |  提交时间：2022/01/24
Character glyph synthesis  Decoupled representation  generative adversarial networks  
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：411/90  |  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  
Baselines Extraction from Curved Document Images via Slope Fields Recovery 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2020, 卷号: 42, 期号: 4, 页码: 793-808
作者:  Meng, Gaofeng;  Pan, Chunhong;  Xiang, Shiming;  Wu, Ying
浏览  |  Adobe PDF(15645Kb)  |  收藏  |  浏览/下载：221/47  |  提交时间：2020/06/02
Estimation  Image segmentation  Layout  Distortion  Strips  Image quality  Degradation  Document image processing  curved baselines extraction  slope fields recovery  geometric distortion rectification  
A Performance Evaluation of Local Features for Image-Based 3D Reconstruction 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2019, 卷号: 28, 期号: 10, 页码: 4774-4789
作者:  Fan, Bin;  Kong, Qingqun;  Wang, Xinchao;  Wang, Zhiheng;  Xiang, Shiming;  Pan, Chunhong;  Fua, Pascal
浏览  |  Adobe PDF(3986Kb)  |  收藏  |  浏览/下载：330/70  |  提交时间：2019/12/16
Local feature  image reconstruction  structure from motion (SFM)  3D vision  image matching  
Weakly Semantic Guided Action Recognition 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2019, 卷号: 21, 期号: 10, 页码: 2504-2517
作者:  Yu, Tingzhao;  Wang, Lingfeng;  Da, Cheng;  Gu, Huxiang;  Xiang, Shiming;  Pan, Chunhong
Adobe PDF(18774Kb)  |  收藏  |  浏览/下载：435/112  |  提交时间：2019/05/15
Semantic guided module  action recognition  cross domain  3D convolution  attention model  
Joint spatial temporal attention for action recognition 期刊论文
Pattern Recognition Letters, 2018, 期号: 112, 页码: 226-233
作者:  Tingzhao Yu;  Chaoxu Guo;  Lingfeng Wang;  Huxiang Gu;  Shiming Xiang;  Chunhong Pan
浏览  |  Adobe PDF(1133Kb)  |  收藏  |  浏览/下载：422/189  |  提交时间：2019/05/06
Action Recognition  Spatial-temporal Attention  Two-stage  
Deep unsupervised learning with consistent inference of latent representations 期刊论文
PATTERN RECOGNITION, 2018, 卷号: 77, 期号: 5, 页码: 438-453
作者:  Chang, Jianlong;  Wang, Lingfeng;  Meng, Gaofeng;  Xiang, Shiming;  Pan, Chunhong
浏览  |  Adobe PDF(2654Kb)  |  收藏  |  浏览/下载：448/171  |  提交时间：2018/01/16
Deep Unsupervised Learning  Consistent Inference Of Latent Representations  
Aggregating Rich Hierarchical Features for Scene Classification in Remote Sensing Imagery 期刊论文
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2017, 卷号: 10, 期号: 9, 页码: 4104-4115
作者:  Wang, Guoli;  Fan, Bin;  Xiang, Shiming;  Pan, Chunhong
Adobe PDF(878Kb)  |  收藏  |  浏览/下载：519/217  |  提交时间：2017/05/09
Convolutional Neural Networks (Cnns)  Mixed-resolution Representation  Remote Sensing Scene Classification  Vector Of Locally Aggregated Descriptors (Vlad)  
Image tag-ranking via pairwise supervision based semi-supervised model 期刊论文
NEUROCOMPUTING, 2015, 卷号: 167, 页码: 614-624
作者:  He, Yonghao;  Kang, Cuicui;  Wang, Jian;  Xiang, Shiming;  Pan, Chunhong
浏览  |  Adobe PDF(1512Kb)  |  收藏  |  浏览/下载：360/119  |  提交时间：2015/09/23
Image Tag-ranking  Pairwise Supervision  Learning To Rank