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Two-stream network for infrared and visible images fusion 期刊论文
Neurocomputing, 2021, 卷号: 460, 页码: 50-58
作者:  Liu, Luolin;  Chen, Mulin;  Xu, Mingliang;  Li, Xuelong
Adobe PDF(3505Kb)  |  收藏  |  浏览/下载：217/0  |  提交时间：2021/09/06
Image fusion  Infrared image  Thermal image  Two-stream network  
Density saliency for clustered building detection and population capacity estimation 期刊论文
Neurocomputing, 2021, 卷号: 458, 页码: 127-140
作者:  Liu, Kang;  Huang, Ju;  Xu, Mingliang;  Perc, Matja;  Li, Xuelong
Adobe PDF(5204Kb)  |  收藏  |  浏览/下载：221/0  |  提交时间：2021/09/06
Remote sensing  Clustered Building Detection (CBD)  Saliency heatmap  Deep Neural Network (DNN)  Population Capacity Estimation (PCE)  
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
Discriminative and orthogonal subspace constraints-based nonnegative matrix factorization 期刊论文
ACM Transactions on Intelligent Systems and Technology, 2018, 卷号: 9, 期号: 6
作者:  Li, Xuelong;  Cui, Guosheng;  Dong, Yongsheng
Adobe PDF(2717Kb)  |  收藏  |  浏览/下载：173/0  |  提交时间：2019/03/04
A Coarse-to-Fine Semi-Supervised Change Detection for Multispectral Images 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2018, 卷号: 56, 期号: 6, 页码: 3587-3599
作者:  Zhang, Wuxia;  Lu, Xiaoqiang;  Li, Xuelong;  Lu, XQ (reprint author), Chinese Acad Sci, Xian Inst Opt & Precis Mech, Ctr Opt Imagery Anal & Learning OPTIMAL, Xian 710119, Shaanxi, Peoples R China.
Adobe PDF(3641Kb)  |  收藏  |  浏览/下载：252/1  |  提交时间：2018/06/28
Change Detection  Keep It Simple And Straight-forward (Kiss) Metric Learning  Multiscale Feature  Multispectral Imagery  Semi-supervised Learning  
SCE: A Manifold Regularized Set-Covering Method for Data Partitioning 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 期号: 5, 页码: 1760-1773
作者:  Li, Xuelong;  Lu, Quanmao;  Dong, Yongsheng;  Tao, Dacheng;  Dong, YS (reprint author), Chinese Acad Sci, Xian Inst Opt & Precis Mech, OPT IMagery Anal & Learning OPTIMAL, State Key Lab Transient Opt & Photon, Xian 710119, Shaanxi, Peoples R China.
Adobe PDF(3328Kb)  |  收藏  |  浏览/下载：250/1  |  提交时间：2018/05/14
Cluster Ensemble  Discriminative Constraint  Manifold Structure  Set Covering  
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：211/1  |  提交时间：2018/04/11
Class Compactness Graph  Computer Vision  Label Relaxation  Linear Regression (Lr)  Manifold Learning  
PixelLink: Detecting scene text via instance segmentation 会议论文
32nd AAAI Conference on Artificial Intelligence, AAAI 2018, New Orleans, LA, United states, 2018-02-02
作者:  Deng, Dan;  Liu, Haifeng;  Li, Xuelong;  Cai, Deng
浏览  |  Adobe PDF(798Kb)  |  收藏  |  浏览/下载：169/0  |  提交时间：2019/03/22
Unsupervised 3D Local Feature Learning by Circle Convolutional Restricted Boltzmann Machine 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2016, 卷号: 25, 期号: 11, 页码: 5331-5344
作者:  Han, Zhizhong;  Liu, Zhenbao;  Han, Junwei;  Vong, Chi-Man;  Bu, Shuhui;  Li, Xuelong;  Liu, Zhenbao (liuzhenbao@nwpu.edu.cn)
浏览  |  Adobe PDF(3347Kb)  |  收藏  |  浏览/下载：323/1  |  提交时间：2016/10/09
Circle Convolutional Restricted Boltzmann Machine  Deep Learning  Projection Distance Distribution  Geometry Processing  Fourier Transform Modulus  3d Shapes  
Detection of Co-salient Objects by Looking Deep and Wide 期刊论文
INTERNATIONAL JOURNAL OF COMPUTER VISION, 2016, 卷号: 120, 期号: 2, 页码: 215-232
作者:  Zhang, Dingwen;  Han, Junwei;  Li, Chao;  Wang, Jingdong;  Li, Xuelong;  Han, JW
Adobe PDF(7504Kb)  |  收藏  |  浏览/下载：420/1  |  提交时间：2016/11/14
Co-saliency Detection  Domain Adaptive Convolutional Neural Network  Bayesian Framework