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Neural & Bio-inspired Processing and Robot Control 期刊论文
FRONTIERS IN NEUROROBOTICS, 2018, 卷号: 12, 页码: 2
作者:  Khan, Ameer Hamza;  Li, Shuai;  Zhou, Xuefeng;  Li, Yangming;  Khan, Muhammad Umer;  Luo, Xin;  Wang, Huanqing
Adobe PDF(159Kb)  |  收藏  |  浏览/下载：172/0  |  提交时间：2018/12/13
bio-inspired  robot control  neural processing  processing  intelligent algorithm  
Spatio-Temporal Patterns and Impacts of Sediment Variations in Downstream of the Three Gorges Dam on the Yangtze River, China 期刊论文
SUSTAINABILITY, 2018, 卷号: 10, 期号: 11, 页码: 17
作者:  Chen, Jilong;  Fang, Xinrui;  Wen, Zhaofei;  Chen, Qiao;  Ma, Maohua;  Huang, Yuanyang;  Wu, Shengjun;  Yang, Liang Emlyn
Adobe PDF(2812Kb)  |  收藏  |  浏览/下载：182/0  |  提交时间：2019/01/17
suspended sediment concentration  Three Gorges Dam  riverbank collapse  impoundment  
Modified Primal-Dual Neural Networks for Motion Control of Redundant Manipulators With Dynamic Rejection of Harmonic Noises 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 期号: 10, 页码: 4791-4801
作者:  Li, Shuai;  Zhou, MengChu;  Luo, Xin
Adobe PDF(2696Kb)  |  收藏  |  浏览/下载：294/0  |  提交时间：2018/11/01
Dual neural network  kinematic control  redundancy resolution  robotic manipulator  
Modified Primal-Dual Neural Networks for Motion Control of Redundant Manipulators With Dynamic Rejection of Harmonic Noises 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 期号: 10, 页码: 4791-4801
作者:  Li, Shuai;  Zhou, MengChu;  Luo, Xin
Adobe PDF(2696Kb)  |  收藏  |  浏览/下载：289/0  |  提交时间：2019/06/26
Dual neural network  kinematic control  redundancy resolution  robotic manipulator  
Semi-supervised spatio-temporal CNN for recognition of surgical workflow 期刊论文
EURASIP Journal on Image and Video Processing, 2018, 卷号: 2018, 期号: 1
作者:  Chen,Yuwen;  Sun,Qi Long;  Zhong,Kunhua
Adobe PDF(2573Kb)  |  收藏  |  浏览/下载：154/0  |  提交时间：2019/01/17
Semi-supervised  Surgical workflow  CNN  
Incorporation of Efficient Second-Order Solvers Into Latent Factor Models for Accurate Prediction of Missing QoS Data 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2018, 卷号: 48, 期号: 4, 页码: 1216-1228
作者:  Luo, Xin;  Zhou, MengChu;  Li, Shuai;  Xia, Yunni;  You, Zhu-Hong;  Zhu, QingSheng;  Leung, Hareton
收藏  |  浏览/下载：519/0  |  提交时间：2018/06/04
Big data  latent factor model  missing data prediction  quality-of-service (QoS)  second-order solver  service computing sparse matrices  Web service  
Towards Robust and Accurate Multi-View and Partially-Occluded Face Alignment 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2018, 卷号: 40, 期号: 4, 页码: 987-1001
作者:  Xing, Junliang;  Niu, Zhiheng;  Huang, Junshi;  Hu, Weiming;  Zhou, Xi;  Yan, Shuicheng
收藏  |  浏览/下载：92/0  |  提交时间：2018/06/04
Face alignment  dictionary learning  sparse representation  appearance-shape modeling  
Extensive exploration of comprehensive vehicle attributes using D-CNN with weighted multi-attribute strategy 期刊论文
IET INTELLIGENT TRANSPORT SYSTEMS, 2018, 卷号: 12, 期号: 3, 页码: 186-193
作者:  Yan, Zhuo;  Feng, Youji;  Cheng, Cheng;  Fu, Jianting;  Zhou, Xiangdong;  Yuan, Jiahu
Adobe PDF(3776Kb)  |  收藏  |  浏览/下载：240/0  |  提交时间：2018/06/04
Object Recognition  Feedforward Neural Nets  Learning (Artificial Intelligence)  Comprehensive Vehicle Attributes  D-cnn  Weighted Multiattribute Strategy  Deep Convolutional Neural Network  Surveillance Images  Vehicle Model Recognition  Make Recognition  Mtl Methods  Multitask Learning  Compcars Vehicle Dataset  Manufacturer Recognition  
Self-training semi-supervised classification based on density peaks of data 期刊论文
NEUROCOMPUTING, 2018, 卷号: 275, 页码: 180-191
作者:  Wu, Di;  Shang, Mingsheng;  Luo, Xin;  Xu, Ji;  Yan, Huyong;  Deng, Weihui;  Wang, Guoyin
收藏  |  浏览/下载：169/0  |  提交时间：2018/03/05
Density peaks  Self-training  Semi-supervised classification  Supervised learning  
Incremental Slope-one recommenders 期刊论文
NEUROCOMPUTING, 2018, 卷号: 272, 页码: 606-618
作者:  Wang, Qing-Xian;  Luo, Xin;  Li, Yan;  Shi, Xiao-Yu;  Gu, Liang;  Shang, Ming-Sheng
收藏  |  浏览/下载：159/0  |  提交时间：2018/03/05
Collaborative Filtering  Slope-one  Recommender System  Dynamic Datasets  Incremental Recommenders