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Local-Aggregation Graph Networks 期刊论文
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019, 期号: 1, 页码: 1
作者:  Chang, Jianlong
浏览  |  Adobe PDF(2735Kb)  |  收藏  |  浏览/下载：232/78  |  提交时间：2020/06/11
Local-aggregation function, local-aggregation graph neural network, non-Euclidean structured signal.  
A Gallery-Guided Graph Architecture for Sequential Impurity Detection 期刊论文
IEEE ACCESS, 2019, 卷号: 7, 期号: 0, 页码: 149105-149116
作者:  He, Wenhao;  Song, Haitao;  Guo, Yue;  Yin, Xiaoyi;  Wang, Xiaonan;  Bian, Guibin;  Qian, Wen
浏览  |  Adobe PDF(3588Kb)  |  收藏  |  浏览/下载：379/68  |  提交时间：2020/03/30
Impurities  Proposals  Feature extraction  Training  Convolutional neural networks  Task analysis  Impurity detection  gallery-guided graph  feature embedding  graph convolutional neural network  
Progress and Outlook of Visual Tracking: Bibliographic Analysis and Perspective 期刊论文
IEEE ACCESS, 2019, 卷号: 7, 页码: 184581-184598
作者:  Liu, Yating;  Wang, Kunfeng;  Li, Xuesong;  Bai, Tianxiang;  Wang, Fei-Yue
Adobe PDF(4276Kb)  |  收藏  |  浏览/下载：234/36  |  提交时间：2020/03/30
Visual tracking  bibliographic analysis  collaboration patterns  research hotspots  parallel vision  
Preoperative Diagnosis of Regional Lymph Node Metastasis of Colorectal Cancer With Quantitative Parameters From Dual-Energy CT 期刊论文
AMERICAN JOURNAL OF ROENTGENOLOGY, 2019, 卷号: 213, 期号: 1, 页码: W17-W25
作者:  Yang, Zehong;  Zhang, Xiang;  Fang, Mengjie;  Li, Guolin;  Duan, Xiaohui;  Mao, Jiaji;  Shen, Jun
Adobe PDF(990Kb)  |  收藏  |  浏览/下载：389/68  |  提交时间：2019/12/16
colorectal neoplasm  diagnostic imaging  lymphadenopathy  MDCT  
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：494/115  |  提交时间：2019/12/16
Deep learning  Graph convolutional neural networks  Graph structure learning  Changeable kernel sizes  
Deep Multi-Modality Adversarial Networks for Unsupervised Domain Adaptation 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2019, 卷号: 21, 期号: 9, 页码: 2419-2431
作者:  Ma, Xinhong;  Zhang, Tianzhu;  Xu, Changsheng
Adobe PDF(2142Kb)  |  收藏  |  浏览/下载：384/49  |  提交时间：2019/12/16
Unsupervised domain adaptation  triplet loss  stacked attention  multi-modality  social event recognition  
Discriminating schizophrenia using recurrent neural network applied on time courses of multi-site FMRI data 期刊论文
EBIOMEDICINE, 2019, 卷号: 47, 页码: 543-552
作者:  Yan, Weizheng;  Calhoun, Vince;  Song, Ming;  Cui, Yue;  Yan, Hao;  Liu, Shengfeng;  Fan, Lingzhong;  Zuo, Nianming;  Yang, Zhengyi;  Xu, Kaibin;  Yan, Jun;  Lv, Luxian;  Chen, Jun;  Chen, Yunchun;  Guo, Hua;  Li, Peng;  Lu, Lin;  Wan, Ping;  Wang, Huaning;  Wang, Huiling;  Yang, Yongfeng;  Zhang, Hongxing;  Zhang, Dai;  Jiang, Tianzi;  Sui, Jing
Adobe PDF(2166Kb)  |  收藏  |  浏览/下载：448/74  |  提交时间：2019/12/16
Recurrent neural network (RNN)  Schizophrenia  Multi-site classification  fMRI  Striatum  Cerebellum  Deep learning  
Two-Level Attention Network With Multi-Grain Ranking Loss for Vehicle Re-Identification 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2019, 卷号: 28, 期号: 9, 页码: 4328-4338
作者:  Guo, Haiyun;  Zhu, Kuan;  Tang, Ming;  Wang, Jinqiao
浏览  |  Adobe PDF(2562Kb)  |  收藏  |  浏览/下载：382/78  |  提交时间：2019/12/16
Two-level attention network  multi-grain ranking loss  vehicle re-identification  feature embedding  
Towards fast and kernelized orthogonal discriminant analysis on person re-identification 期刊论文
Pattern Recognition, 2019, 期号: 94, 页码: 218-229
作者:  Min Cao;  Chen Chen;  Xiyuan Hu;  Silong Peng
浏览  |  Adobe PDF(1700Kb)  |  收藏  |  浏览/下载：325/112  |  提交时间：2019/09/10
Person Re-identificationmetric Learningsingularity Problemorthogonal Discriminant Analysis  
Unsupervised Semantic-Based Aggregation of Deep Convolutional Features 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2019, 卷号: 28, 期号: 2, 页码: 601-611
作者:  Xu, Jian;  Wang, Chunheng;  Qi, Chengzuo;  Shi, Cunzhao;  Xiao, Baihua
浏览  |  Adobe PDF(1963Kb)  |  收藏  |  浏览/下载：421/96  |  提交时间：2019/07/12
Unsupervised  semantic-based aggregation  semantic detectors