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First-in-human liver-tumour surgery guided by multispectral fluorescence imaging in the visible and near-infrared-I/II windows 期刊论文
NATURE BIOMEDICAL ENGINEERING, 2019, 卷号: 4, 期号: 3, 页码: 16
作者:  Hu, Zhenhua;  Fang, Cheng;  Li, Bo;  Zhang, Zeyu;  Cao, Caiguang;  Cai, Meishan;  Su, Song;  Sun, Xingwang;  Shi, Xiaojing;  Li, Cong;  Zhou, Tiejun;  Zhang, Yuanxue;  Chi, Chongwei;  He, Pan;  Xia, Xianming;  Chen, Yue;  Gambhir, Sanjiv Sam;  Cheng, Zhen;  Tian, Jie
Adobe PDF(2918Kb)  |  收藏  |  浏览/下载:434/87  |  提交时间:2020/03/30
A novel hardware-oriented ultra-high-speed object detection algorithm based on convolutional neural network 期刊论文
JOURNAL OF REAL-TIME IMAGE PROCESSING, 2019, 期号: 17, 页码: 1703-1714
作者:  Li, Jianquan;  Long, Xianlei;  Hu, Shenhua;  Hu, Yiming;  Gu, Qingyi;  Xu, De
Adobe PDF(1879Kb)  |  收藏  |  浏览/下载:262/42  |  提交时间:2020/08/03
FPGA implementation  High-speed vision  Fast-object detection  Convolutional neural network  
A novel Cerenkov luminescence tomography approach using multilayer fully connected neural network 期刊论文
Physics in Medicine & Biology, 2019, 卷号: 64, 期号: 2019, 页码: 245010
作者:  Zhang,Zeyu;  Cai,Meishan;  Gao,Yuan;  Shi,Xiaojing;  Zhang,Xiaojun;  Hu,Zhenhua;  Tian,Jie
Adobe PDF(3210Kb)  |  收藏  |  浏览/下载:345/71  |  提交时间:2020/03/30
Cerenkov luminescence tomography (CLT)  optical reconstruction  photon propagation  neural network  inverse problem  
Towards Real-Time Advancement of Underwater Visual Quality With GAN 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2019, 卷号: 66, 期号: 12, 页码: 9350-9359
作者:  Chen, Xingyu;  Yu, Junzhi;  Kong, Shihan;  Wu, Zhengxing;  Fang, Xi;  Wen, Li
浏览  |  Adobe PDF(4984Kb)  |  收藏  |  浏览/下载:396/136  |  提交时间:2019/12/16
Generative adversarial networks (GAN) image restoration  machine learning  underwater vision  
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:276/64  |  提交时间:2020/06/10
Face verification  Makeup transfer  Disentangled feature  Correspondence field  
ISEE: An Intelligent Scene Exploration and Evaluation Platform for Large-Scale Visual Surveillance 期刊论文
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2019, 卷号: 30, 期号: 12, 页码: 2743-2758
作者:  Li, Da;  Zhang, Zhang;  Yu, Kai;  Huang, Kaiqi;  Tan, Tieniu
收藏  |  浏览/下载:269/0  |  提交时间:2020/03/30
Visualization  Surveillance  Task analysis  Streaming media  Computer architecture  Pipelines  Sparks  Intelligent surveillance system  big visual data  distributed system and parallel computing  
Surface Defects Detection Based on Adaptive Multiscale Image Collection and Convolutional Neural Networks 期刊论文
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2019, 卷号: 68, 期号: 12, 页码: 4787-4797
作者:  Sun, Jia;  Wang, Peng;  Luo, Yong-Kang;  Li, Wanyi
浏览  |  Adobe PDF(4530Kb)  |  收藏  |  浏览/下载:244/78  |  提交时间:2020/03/30
Inspection  Surface treatment  Training  Metals  Task analysis  Instruments  Visualization  Adaptive multiscale image collection (AMIC)  convolutional neural networks (CNNs)  image classification  surface inspection  
基于图像纹理的自适应水印算法 期刊论文
北京航空航天大学学报, 2019, 卷号: 45, 期号: 12, 页码: 2403-2414
作者:  黄樱;  牛保宁;  关虎;  张树武
浏览  |  Adobe PDF(1031Kb)  |  收藏  |  浏览/下载:138/54  |  提交时间:2020/10/23
图像水印  图像纹理  不可见性  鲁棒性  自适应性  
Second-Order Sliding Mode Formation Control of Multiple Robots by Extreme Learning Machine 期刊论文
SYMMETRY-BASEL, 2019, 卷号: 11, 期号: 12, 页码: 19
作者:  Qian, Dianwei;  Zhang, Guigang;  Wang, Jian;  Wu, Zhimin
浏览  |  Adobe PDF(3470Kb)  |  收藏  |  浏览/下载:271/47  |  提交时间:2020/03/30
multirobot systems  formation maneuvers  super-twisting sliding mode control  uncertainties  extreme learning machine  
GaitNet: An end-to-end network for gait based human identification 期刊论文
PATTERN RECOGNITION, 2019, 卷号: 96, 期号: 106988, 页码: 11
作者:  Song, Chunfeng;  Huang, Yongzhen;  Huang, Yan;  Jia, Ning;  Wang, Liang
浏览  |  Adobe PDF(3015Kb)  |  收藏  |  浏览/下载:552/153  |  提交时间:2019/12/16
Gait recognition  Video-based human identification  End-to-end CNN  Joint learning