OPT OpenIR
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Ensemble of half-space trees for hyperspectral anomaly detection 期刊论文
SCIENCE CHINA-INFORMATION SCIENCES, 2022, 卷号: 65, 期号: 9
作者:  Huang, Ju;  Li, Xuelong
Adobe PDF(2153Kb)  |  收藏  |  浏览/下载:137/0  |  提交时间:2022/10/10
hyperspectral image  anomaly detection  extended morphological attribute profile  mass estimation  half-space tree  
Eagle-Eye-Inspired Attention for Object Detection in Remote Sensing 期刊论文
REMOTE SENSING, 2022, 卷号: 14, 期号: 7
作者:  Liu, Kang;  Huang, Ju;  Li, Xuelong
Adobe PDF(2850Kb)  |  收藏  |  浏览/下载:146/0  |  提交时间:2022/05/05
remote sensing  object detection  eagle-eye fovea network (EFNet)  anchor-free  attention mechanism  
Hyperspectral Unmixing Using Nonlocal Similarity-Regularized Low-Rank Tensor Factorization 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 卷号: 60
作者:  Yuan, Yuan;  Dong, Le;  Li, Xuelong
Adobe PDF(5662Kb)  |  收藏  |  浏览/下载:244/0  |  提交时间:2022/01/18
Tensors  TV  Hyperspectral imaging  Data models  Task analysis  Optimization  Data mining  Hyperspectral unmixing  low tensor rank  nonlocal similarity  nonnegative tensor factorization (NTF)  
Nonlocal Graph Convolutional Networks for Hyperspectral Image Classification 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2020, 卷号: 58, 期号: 12, 页码: 8246-8257
作者:  Mou, Lichao;  Lu, Xiaoqiang;  Li, Xuelong;  Zhu, Xiao Xiang
Adobe PDF(10395Kb)  |  收藏  |  浏览/下载:252/0  |  提交时间:2020/12/21
Hyperspectral imaging  Convolution  Task analysis  Recurrent neural networks  Semisupervised learning  Support vector machines  Graph convolutional network (GCN)  hyperspectral image classification  nonlocal graph  semisupervised learning  
A Survey of Human Action Analysis in HRI Applications 期刊论文
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2020, 卷号: 30, 期号: 7, 页码: 2114-2128
作者:  Ji, Yanli;  Yang, Yang;  Shen, Fumin;  Shen, Heng Tao;  Li, Xuelong
Adobe PDF(2113Kb)  |  收藏  |  浏览/下载:199/4  |  提交时间:2020/07/20
Human-robot interaction  action recognition  action prediction  action imitation  datasets  robots  
Reconstructing of embedded high-aspect-ratio nano-voids generated by ultrafast laser bessel beams 期刊论文
Micromachines, 2020, 卷号: 11, 期号: 7
作者:  Chen, Tianqu;  Zhang, Guodong;  Wang, Yishan;  Li, Xuelong;  Stoian, Razvan;  Cheng, Guanghua
Adobe PDF(2248Kb)  |  收藏  |  浏览/下载:198/1  |  提交时间:2020/08/21
bessel beam  femtosecond laser  picosecond laser  fused silica  micro-nano hole  high-aspect-ratio  tomography  
Discrete Deep Hashing with Ranking Optimization for Image Retrieval 期刊论文
IEEE Transactions on Neural Networks and Learning Systems, 2020, 卷号: 31, 期号: 6, 页码: 2052-2063
作者:  Lu, Xiaoqiang;  Chen, Yaxiong;  Li, Xuelong
Adobe PDF(3191Kb)  |  收藏  |  浏览/下载:206/2  |  提交时间:2020/06/24
Category-level Information  discrete deep hashing  image retrieval  ranking information  
Design and fabrication of dual-scale broadband antireflective structures on metal surfaces by using nanosecond and femtosecond lasers 期刊论文
Micromachines, 2020, 卷号: 11, 期号: 1
作者:  Lou, Rui;  Zhang, Guodong;  Li, Guangying;  Li, Xuelong;  Liu, Qing;  Cheng, Guanghua
Adobe PDF(3104Kb)  |  收藏  |  浏览/下载:195/4  |  提交时间:2020/03/10
antireflective surfaces  nanosecond laser  femtosecond laser  micro-nano hybrid structures  broadband spectrum  
Unsupervised learning of human action categories in still images with deep representations 期刊论文
ACM Transactions on Multimedia Computing, Communications and Applications, 2019, 卷号: 15, 期号: 4
作者:  Zheng, Yunpeng;  Li, Xuelong;  Lu, Xiaoqiang
Adobe PDF(23484Kb)  |  收藏  |  浏览/下载:212/2  |  提交时间:2020/01/17
Action categorization  unsupervised learning  deep representations  
Does being multi-headed make you better at solving problems? A survey of Physarum-based models and computations 期刊论文
PHYSICS OF LIFE REVIEWS, 2019, 卷号: 29, 页码: 1-26
作者:  Gao, Chao;  Liu, Chen;  Schenz, Daniel;  Li, Xuelong;  Zhang, Zili;  Jusup, Marko;  Wang, Zhen;  Beekman, Madeleine;  Nakagaki, Toshiyuki
Adobe PDF(4064Kb)  |  收藏  |  浏览/下载:179/0  |  提交时间:2019/09/24
Modelling and computation  Bio-inspired computing  Physarum polycephalum  Intelligent behaviour  Complex problem solving