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TTH-RNN: Tensor-Train Hierarchical Recurrent Neural Network for Video Summarization 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2021, 卷号: 68, 期号: 4, 页码: 3629-3637
作者:  Zhao, Bin;  Li, Xuelong;  Lu, Xiaoqiang
Adobe PDF(1796Kb)  |  收藏  |  浏览/下载：215/0  |  提交时间：2021/01/07
Recurrent neural networks  Training  Task analysis  Tensors  Matrix decomposition  Standards  Feature extraction  Hierarchical structure  tensor-train embedding layer  video summarization  
Tilt Correction Towards Building Detection of Remote Sensing Images 期刊论文
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021, 卷号: 14, 页码: 5854-5866
作者:  Liu, Kang;  Jiang, Zhiyu;  Xu, Mingliang;  Perc, Matjaz;  Li, Xuelong
Adobe PDF(8821Kb)  |  收藏  |  浏览/下载：165/0  |  提交时间：2021/06/22
Building detection  cost of building partition (CoBP)  deep neural network (DNN)  remote sensing  tilt correction (TC)  
Robust Subspace Clustering by Cauchy Loss Function 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2019, 卷号: 30, 期号: 7, 页码: 2067-2078
作者:  Li, Xuelong;  Lu, Quanmao;  Dong, Yongsheng;  Tao, Dacheng
Adobe PDF(3374Kb)  |  收藏  |  浏览/下载：266/0  |  提交时间：2019/07/17
Cauchy loss function (CLF)  grouping effect  noise suppression  similarity matrix  subspace clustering  
Joint Learning of Fuzzy k-Means and Nonnegative Spectral Clustering With Side Information 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2019, 卷号: 28, 期号: 5, 页码: 2152–2162
作者:  Zhang, Rui;  Nie, Feiping;  Guo, Muhan;  Wei, Xian;  Li, Xuelong
Adobe PDF(2331Kb)  |  收藏  |  浏览/下载：302/1  |  提交时间：2019/03/20
Fuzzy K-means  spectral clustering  adaptive loss function  
Long-Short-Term Features for Dynamic Scene Classification 期刊论文
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2019, 卷号: 29, 期号: 4, 页码: 1038-1047
作者:  Huang, Yuanjun;  Cao, Xianbin;  Wang, Qi;  Zhang, Baochang;  Zhen, Xiantong;  Li, Xuelong
Adobe PDF(2016Kb)  |  收藏  |  浏览/下载：275/0  |  提交时间：2019/04/30
Dynamic scene classification  long-short term feature  long term frequency feature  
Co-occurrence matching of local binary patterns for improving visual adaption and its application to smoke recognition 期刊论文
IET COMPUTER VISION, 2019, 卷号: 13, 期号: 2(SI), 页码: 178-187
作者:  Yuan, Feiniu;  Shi, Jinting;  Xia, Xue;  Huang, Qinghua;  Li, Xuelong
Adobe PDF(2509Kb)  |  收藏  |  浏览/下载：199/0  |  提交时间：2019/03/14
Shape-Preserving Object Depth Control for Stereoscopic Images 期刊论文
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2018, 卷号: 28, 期号: 12, 页码: 3333-3344
作者:  Lei, Jianjun;  Peng, Bo;  Zhang, Changqing;  Mei, Xuguang;  Cao, Xiaochun;  Fan, Xiaoting;  Li, Xuelong
Adobe PDF(6135Kb)  |  收藏  |  浏览/下载：192/0  |  提交时间：2018/12/28
Depth Control  Depth Mapping Model  Shape Preserving  Stereoscopic Image  Warping Technology  3-d Display  
Zero-Shot Learning Using Synthesised Unseen Visual Data with Diffusion Regularisation 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2018, 卷号: 40, 期号: 10, 页码: 2498-2512
作者:  Long, Yang;  Liu, Li;  Shen, Fumin;  Shao, Ling;  Li, Xuelong
Adobe PDF(1288Kb)  |  收藏  |  浏览/下载：241/1  |  提交时间：2018/10/12
Zero-shot Learning  Data Synthesis  Diffusion Regularisation  Visual-semantic Embedding  Object Recognition  
Perceptually Aware Image Retargeting for Mobile Devices 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2018, 卷号: 27, 期号: 5, 页码: 2301-2313
作者:  Zhou, Yinzuo;  Zhang, Luming;  Zhang, Chao;  Li, Ping;  Li, Xuelong
Adobe PDF(3015Kb)  |  收藏  |  浏览/下载：249/1  |  提交时间：2018/12/11
Mobile Platform  Retarget  Perceptual  Gaze Behavior  Deep Feature  Probabilistic Model  
Regularized Label Relaxation Linear Regression 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 期号: 4, 页码: 1006-1018
作者:  Fang, Xiaozhao;  Xu, Yong;  Li, Xuelong;  Lai, Zhihui;  Wong, Wai Keung;  Fang, Bingwu;  Xu, Y (reprint author), Harbin Inst Technol, Shenzhen Grad Sch, Biocomp Res Ctr, Shenzhen 518055, Peoples R China.
Adobe PDF(3718Kb)  |  收藏  |  浏览/下载：210/1  |  提交时间：2018/04/11
Class Compactness Graph  Computer Vision  Label Relaxation  Linear Regression (Lr)  Manifold Learning