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CASIA OpenIR
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Deep representation learning for domain generalization with information bottleneck principle 期刊论文
PATTERN RECOGNITION, 2023, 卷号: 143, 页码: 12
作者:  Zhang, Jiao;  Zhang, Xu-Yao;  Wang, Chuang;  Liu, Cheng-Lin
收藏  |  浏览/下载：97/0  |  提交时间：2023/11/17
Domain generalization  Information bottleneck  Representation learning  
Adversarial training with distribution normalization and margin balance 期刊论文
PATTERN RECOGNITION, 2023, 卷号: 136, 页码: 11
作者:  Cheng, Zhen;  Zhu, Fei;  Zhang, Xu-Yao;  Liu, Cheng-Lin
收藏  |  浏览/下载：239/0  |  提交时间：2023/01/09
Adversarial robustness  Adversarial training  Distribution normalization  Margin balance  
Towards prior gap and representation gap for long-tailed recognition 期刊论文
PATTERN RECOGNITION, 2023, 卷号: 133, 页码: 12
作者:  Zhang, Ming-Liang;  Zhang, Xu-Yao;  Wang, Chuang;  Liu, Cheng-Lin
收藏  |  浏览/下载：264/0  |  提交时间：2022/11/14
Long-tailed learning  Prior gap  Representation gap  Image recognition  
Cycle-Consistent Weakly Supervised Visual Grounding With Individual and Contextual Representations 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2023, 卷号: 32, 页码: 5167-5180
作者:  Zhang, Ruisong;  Wang, Chuang;  Liu, Cheng-Lin
收藏  |  浏览/下载：105/0  |  提交时间：2023/11/16
Visualization  Grounding  Task analysis  Sports equipment  Image reconstruction  Transformers  Training  Weakly supervised learning  visual grounding  cycle consistency  individual and contextual representations  
Table Structure Recognition and Form Parsing by End-to-End Object Detection and Relation Parsing 期刊论文
PATTERN RECOGNITION, 2022, 卷号: 132, 页码: 14
作者:  Li, Xiao-Hui;  Yin, Fei;  Dai, He-Sen;  Liu, Cheng-Lin
收藏  |  浏览/下载：234/0  |  提交时间：2022/11/14
Table detection  Table structure recognition  Template -free form parsing  Graph neural network  End -to -end training  
Adaptable Global Network for Whole-Brain Segmentation with Symmetry Consistency Loss 期刊论文
COGNITIVE COMPUTATION, 2022, 页码: 14
作者:  Zhao, Yuan-Xing;  Zhang, Yan-Ming;  Song, Ming;  Liu, Cheng-Lin
Adobe PDF(2496Kb)  |  收藏  |  浏览/下载：277/73  |  提交时间：2022/07/25
Whole-brain segmentation  Adaptable global network  Semi-supervised learning  Symmetry consistency loss  
Mixed-Supervised Scene Text Detection With Expectation-Maximization Algorithm 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2022, 卷号: 31, 页码: 5513-5528
作者:  Zhao, Mengbiao;  Feng, Wei;  Yin, Fei;  Zhang, Xu-Yao;  Liu, Cheng-Lin
Adobe PDF(5999Kb)  |  收藏  |  浏览/下载：312/35  |  提交时间：2022/09/19
Costs  Annotations  Training  Labeling  Detectors  Data models  Benchmark testing  Mixed-supervised learning  scene text detection  weak supervision forms  expectation-maximization algorithm  
Deep Neural Network Self-Distillation Exploiting Data Representation Invariance 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 卷号: 33, 期号: 1, 页码: 257-269
作者:  Xu, Ting-Bing;  Liu, Cheng-Lin
收藏  |  浏览/下载：187/0  |  提交时间：2022/02/16
Training  Nonlinear distortion  Data models  Neural networks  Knowledge engineering  Network architecture  Generalization error  network compression  representation invariance  self-distillation (SD)  
Instance GNN: A Learning Framework for Joint Symbol Segmentation and Recognition in Online Handwritten Diagrams 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2022, 卷号: 24, 页码: 2580-2594
作者:  Yun, Xiao-Long;  Zhang, Yan-Ming;  Yin, Fei;  Liu, Cheng-Lin
收藏  |  浏览/下载：225/0  |  提交时间：2022/07/25
Handwriting recognition  Task analysis  Grammar  Semantics  Image segmentation  Trajectory  Text recognition  Online handwritten diagram recognition  symbol segmentation  symbol recognition  freehand sketch analysis  graph neural networks  
BlockQNN: Efficient Block-Wise Neural Network Architecture Generation 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2021, 卷号: 43, 期号: 7, 页码: 2314-2328
作者:  Zhong, Zhao;  Yang, Zichen;  Deng, Boyang;  Yan, Junjie;  Wu, Wei;  Shao, Jing;  Liu, Cheng-Lin
收藏  |  浏览/下载：234/0  |  提交时间：2021/11/03
Computer architecture  Task analysis  Neural networks  Network architecture  Graphics processing units  Acceleration  Indexes  Convolutional neural network  neural architecture search  AutoML  reinforcement learning  Q-learning