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Towards High Fidelity Face Frontalization in the Wild 期刊论文
International Journal of Computer Vision, 2019, 卷号: 128, 期号: 1, 页码: 1485–1504
作者:  Cao, Jie;  Hu, Yibo;  Zhang, Hongwen;  He, Ran;  Sun, Zhenan
Adobe PDF(3816Kb)  |  收藏  |  浏览/下载：150/40  |  提交时间：2021/05/26
Face frontalization  Realistic face generation  Pose-invariant face recognition  
A Wide Learning Approach for Interpretable Feature Recommendation for 1-D Sensor Data in IoT Analytics 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 6, 页码: 800-811
作者:  Snehasis Banerjee;  Tanushyam Chattopadhyay;  Utpal Garain
浏览  |  Adobe PDF(891Kb)  |  收藏  |  浏览/下载：186/56  |  提交时间：2021/02/22
Feature engineering  sensor data analysis  Internet of things (IoT) analytics  interpretable learning  automation.  
Zero-shot Fine-grained Classification by Deep Feature Learning with Semantics 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 5, 页码: 563-574
作者:  Ao-Xue Li;  Ke-Xin Zhang;  Li-Wei Wang
浏览  |  Adobe PDF(1089Kb)  |  收藏  |  浏览/下载：180/54  |  提交时间：2021/02/22
Fine-grained image classification  zero-shot learning  deep feature learning  domain adaptation  semantic graph.  
Semi-supervised Ladder Networks for Speech Emotion Recognition 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 4, 页码: 437-448
作者:  Tao, Jianhua;  Huang, Jian;  Li, Ya;  Lian, Zheng;  Niu, Mingyue
浏览  |  Adobe PDF(1025Kb)  |  收藏  |  浏览/下载：277/63  |  提交时间：2020/06/20
Speech emotion recognition  the ladder network  semi-supervised learning  autoencoder  regularization  
Learning a bi-level adversarial network with global and local perception for makeup-invariant face verification 期刊论文
Pattern Recognition, 2019, 卷号: 90, 期号: -, 页码: 99-108
作者:  Li, Yi;  Song, Lingxiao;  Wu, Xiang;  He, Ran;  Tan, Tieniu
浏览  |  Adobe PDF(2555Kb)  |  收藏  |  浏览/下载：225/65  |  提交时间：2020/06/10
Face verification  Makeup-invariant  Generative adversarial network  
Disentangled Representation Learning of Makeup Portraits in the Wild 期刊论文
International Journal of Computer Vision, 2019, 卷号: -, 期号: -, 页码: -
作者:  Li, Yi;  Huang, Huaibo;  Cao, Jie;  He, Ran;  Tan, Tieniu
浏览  |  Adobe PDF(24456Kb)  |  收藏  |  浏览/下载：288/64  |  提交时间：2020/06/10
Face verification  Makeup transfer  Disentangled feature  Correspondence field  
Attention-based Convolutional Approach for Misinformation Identification from Massive and Noisy Microblog Posts 期刊论文
computers & security, 2019, 期号: 83, 页码: 106-121
作者:  Yu, Feng;  Liu, Qiang;  Wu, Shu;  Wang, Liang;  Tan, Tieniu
浏览  |  Adobe PDF(1601Kb)  |  收藏  |  浏览/下载：250/98  |  提交时间：2020/06/08
information security  social network  misinformation identification  early detection  convolutional neural network  
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：328/56  |  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  
Progressive Joint Framework for Chinese Question Entity Discovery and Linking With Question Representations 期刊论文
IEEE ACCESS, 2019, 卷号: 7, 期号: -, 页码: 146282-146300
作者:  Lin, Ziqi;  Zhang, Haidong;  Ni, Wancheng;  Yang, Yiping
Adobe PDF(3302Kb)  |  收藏  |  浏览/下载：296/74  |  提交时间：2020/03/30
Entity discovery and linking  information extraction  joint method  natural language processing  question representation model  
A Novel and Efficient CVAE-GAN-Based Approach With Informative Manifold for Semi-Supervised Anomaly Detection 期刊论文
IEEE ACCESS, 2019, 卷号: 2019, 期号: 7, 页码: 88903-88916
作者:  Bian, Jiang;  Hui, Xiaolong;  Sun, Shiying;  Zhao, Xiaoguang;  Tan, Min
浏览  |  Adobe PDF(31078Kb)  |  收藏  |  浏览/下载：323/47  |  提交时间：2019/12/16
Semi-supervised anomaly detection  conditional variational auto-encoder  generative adversarial networks  informative manifold  structural similarity loss