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MCFINet: Multidepth Convolution Network With Shallow-Deep Feature Integration for Semantic Labeling in Remote Sensing Images 期刊论文
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2021, 页码: 5
作者:  Wang, Dongji;  Dong, Qiulei
收藏  |  浏览/下载：132/0  |  提交时间：2022/01/27
Labeling  Convolution  Semantics  Feature extraction  Remote sensing  Kernel  Fuses  Convolutional neural networks  multiscale contexts  remote sensing images  semantic labeling  
MRDDANet: A Multiscale Residual Dense Dual Attention Network for SAR Image Denoising 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2021, 页码: 13
作者:  Liu, Shuaiqi;  Lei, Yu;  Zhang, Luyao;  Li, Bing;  Hu, Weiming;  Zhang, Yu-Dong
收藏  |  浏览/下载：202/0  |  提交时间：2022/01/27
Noise reduction  Radar polarimetry  Feature extraction  Speckle  Transforms  Synthetic aperture radar  Image denoising  Dual attention network  feature extraction  multiscale  synthetic aperture radar (SAR) image denoising  
Convolutional Ordinal Regression Forest for Image Ordinal Estimation 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 12
作者:  Zhu, Haiping;  Shan, Hongming;  Zhang, Yuheng;  Che, Lingfu;  Xu, Xiaoyang;  Zhang, Junping;  Shi, Jianbo;  Wang, Fei-Yue
收藏  |  浏览/下载：214/0  |  提交时间：2022/01/27
Decision trees  Estimation  Task analysis  Forestry  Vegetation  Random forests  Support vector machines  Differentiable decision trees  image ordinal estimation  ordinal distribution learning  ordinal regression (OR)  random forest  
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：192/48  |  提交时间：2022/01/24
Character glyph synthesis  Decoupled representation  generative adversarial networks  
Learning Dual-Pooling Graph Neural Networks for Few-Shot Video Classification 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2021, 卷号: 23, 页码: 4285-4296
作者:  Hu, Yufan;  Gao, Junyu;  Xu, Changsheng
收藏  |  浏览/下载：152/0  |  提交时间：2021/12/28
Task analysis  Feature extraction  Training  Testing  Streaming media  Data models  Semantics  Few-shot learning  graph neural networks  video classification  
Emotion Knowledge Driven Video Highlight Detection 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2021, 卷号: 23, 页码: 3999-4013
作者:  Qi, Fan;  Yang, Xiaoshan;  Xu, Changsheng
收藏  |  浏览/下载：210/0  |  提交时间：2021/12/28
Visualization  Training data  Predictive models  Training  Semantics  Emotion recognition  Computational modeling  Deep ranking  knowledge graph  video highlight detection  
Multi-View Feature Selection for PolSAR Image Classification via l(2,1) Sparsity Regularization and Manifold Regularization 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2021, 卷号: 30, 页码: 8607-8618
作者:  Huang, Xiayuan;  Nie, Xiangli
收藏  |  浏览/下载：146/0  |  提交时间：2021/12/28
Multi-view feature selection  PolSAR image classification  l(2,1) norm  manifold regularization  
Transformers in computational visual media: A survey 期刊论文
Computational Visual Media, 2021, 卷号: 8, 期号: 1, 页码: 33-62
作者:  Xu,Yifan;  Wei,Huapeng;  Lin,Minxuan;  Deng,Yingying;  Sheng,Kekai;  Zhang,Mengdan;  Tang,Fan;  Dong,Weiming;  Huang,Feiyue;  Xu,Changsheng
Adobe PDF(5366Kb)  |  收藏  |  浏览/下载：291/38  |  提交时间：2021/12/28
visual transformer  computational visual media (CVM)  high-level vision  low-level vision  image generation  multi-modal learning  
Handwritten Text Generation via Disentangled Representations 期刊论文
IEEE SIGNAL PROCESSING LETTERS, 2021, 卷号: 28, 期号: 2021, 页码: 1838-1842
作者:  Liu, Xiyan;  Meng, Gaofeng;  Xiang, Shiming;  Pan, Chunhong
Adobe PDF(1272Kb)  |  收藏  |  浏览/下载：278/64  |  提交时间：2021/11/04
Disentangled representation  Handwritten text generation  
Learning to Model Relationships for Zero-Shot Video Classification 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2021, 卷号: 43, 期号: 10, 页码: 3476-3491
作者:  Gao, Junyu;  Zhang, Tianzhu;  Xu, Changsheng
收藏  |  浏览/下载：261/0  |  提交时间：2021/11/04
Zero-shot video classification  graph neural networks  zero-shot learning  deep attention model