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Exploring Explicitly Disentangled Features for Domain Generalization 期刊论文
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2023, 卷号: 33, 期号: 11, 页码: 6360-6373
作者:  Li, Jingwei;  Li, Yuan;  Wang, Huanjie;  Liu, Chengbao;  Tan, Jie
收藏  |  浏览/下载：72/0  |  提交时间：2023/12/21
Domain generalization  feature disentanglement  Fourier transform  data augmentation  
Optimization-Based Post-Training Quantization With Bit-Split and Stitching 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2023, 卷号: 45, 期号: 2, 页码: 2119-2135
作者:  Wang, Peisong;  Chen, Weihan;  He, Xiangyu;  Chen, Qiang;  Liu, Qingshan;  Cheng, Jian
Adobe PDF(921Kb)  |  收藏  |  浏览/下载：168/48  |  提交时间：2023/03/20
Deep neural networks  compression  quantization  post-training quantization  
ASCL: Adversarial supervised contrastive learning for defense against word substitution attacks 期刊论文
NEUROCOMPUTING, 2022, 卷号: 510, 页码: 59-68
作者:  Shi, Jiahui;  Li, Linjing;  Zeng, Daniel
Adobe PDF(1054Kb)  |  收藏  |  浏览/下载：224/25  |  提交时间：2022/11/14
Adversarial example  Adversarial training  Model robustness  Contrastive learning  Natural language processing  
Meta Graph Transformer: A Novel Framework for Spatial-Temporal Traffic Prediction 期刊论文
NEUROCOMPUTING, 2022, 卷号: 491, 页码: 544-563
作者:  Ye, Xue;  Fang, Shen;  Sun, Fang;  Zhang, Chunxia;  Xiang, Shiming
Adobe PDF(3491Kb)  |  收藏  |  浏览/下载：221/26  |  提交时间：2022/09/19
Traffic prediction  Spatial-temporal modeling  Meta-learning  Attention mechanism  Deep learning  
Using Pre-trained Language Model to Enhance Active Learning for Sentence Matching 期刊论文
ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING, 2022, 卷号: 21, 期号: 2, 页码: 19
作者:  Bai, Guirong;  He, Shizhu;  Liu, Kang;  Zhao, Jun
Adobe PDF(4097Kb)  |  收藏  |  浏览/下载：263/52  |  提交时间：2022/06/10
Sentence matching  active learning  pre-trained language model  
Theme-Aware Aesthetic Distribution Prediction With Full-Resolution Photographs 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 页码: 15
作者:  Jia, Gengyun;  Li, Peipei;  He, Ran
Adobe PDF(10845Kb)  |  收藏  |  浏览/下载：242/34  |  提交时间：2022/06/06
Aesthetic quality assessment (AQA)  full resolution  region of image (RoM) pooling  theme  
Question-Guided Erasing-Based Spatiotemporal Attention Learning for Video Question Answering 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 0
作者:  Liu, Fei;  Liu, Jing;  Hong, Richang;  Lu, Hanqing
Adobe PDF(3550Kb)  |  收藏  |  浏览/下载：318/78  |  提交时间：2022/01/27
video question answering  attention mechanism  metric learning  
Trip Purposes Mining From Mobile Signaling Data 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2021, 卷号: 99, 期号: 99, 页码: 13
作者:  Li, Zhishuai;  Xiong, Gang;  Wei, Zebing;  Zhang, Yu;  Zheng, Meng;  Liu, Xiaoli;  Tarkoma, Sasu;  Huang, Min;  Lv, Yisheng;  Wu, Chuheng
Adobe PDF(3962Kb)  |  收藏  |  浏览/下载：376/71  |  提交时间：2022/01/27
Cellular networks  Trajectory  Semantics  Unsupervised learning  Supervised learning  Resource management  Public transportation  Trip purpose inference  cellular network data  latent Dirichlet allocation  travel behavior  big data  
Partial NIR-VIS Heterogeneous Face Recognition With Automatic Saliency Search 期刊论文
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2021, 卷号: 16, 页码: 5003-5017
作者:  Luo, Mandi;  Ma, Xin;  Li, Zhihang;  Cao, Jie;  He, Ran
Adobe PDF(4346Kb)  |  收藏  |  浏览/下载：268/55  |  提交时间：2021/12/28
Face recognition  Task analysis  Visualization  Image recognition  Lighting  Feature extraction  Training  Heterogeneous face recognition  near infrared-visible matching  information bottleneck  neural architecture search  
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：280/35  |  提交时间：2021/12/28
visual transformer  computational visual media (CVM)  high-level vision  low-level vision  image generation  multi-modal learning