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CASIA OpenIR
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PCUNet: A Context-Aware Deep Network for Coarse-to-Fine Point Cloud Completion 期刊论文
IEEE Sensors Journal, 2022, 卷号: 22, 期号: 15, 页码: 15098-15110
作者:  Zhao, Meihua;  Xiong, Gang;  Zhou, MengChu;  Shen, Zhen;  Liu, Sheng;  Han, Yunjun;  Wang, Fei-Yue
Adobe PDF(4497Kb)  |  收藏  |  浏览/下载：160/29  |  提交时间：2023/06/27
Asynchronous Threshold ECDSA With Batch Processing 期刊论文
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS, 2023, 页码: 10
作者:  Zhang, Hongxin;  Xie, Guanghuan;  Zou, Xin;  Zhang, Chi;  Li, Zhuo;  Qin, Rui;  Xiong, Gang;  Wang, Fei-Yue
收藏  |  浏览/下载：140/0  |  提交时间：2023/03/20
Protocols  Peer-to-peer computing  Batch production systems  Digital signatures  Blockchains  Electronic mail  Urban areas  Blockchain  crypto-asset custody  secure multiparty computation (MPC)  threshold signature  
A Multi-Agent Reinforcement Learning Method With Route Recorders for Vehicle Routing in Supply Chain Management 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 页码: 11
作者:  Ren, Lei;  Fan, Xiaoyang;  Cui, Jin;  Shen, Zhen;  Lv, Yisheng;  Xiong, Gang
收藏  |  浏览/下载：194/0  |  提交时间：2022/06/06
Reinforcement learning  Costs  Task analysis  Transportation  Optimization  Computational modeling  Vehicle routing  Vehicle routing  supply chain management  multi-agent reinforcement learning (MARL)  route recorder  
基于稀疏正则化的卷积神经网络模型剪枝方法 期刊论文
计算机工程, 2021, 卷号: 47, 期号: 10, 页码: 61-66
作者:  韦越;  陈世超;  朱凤华;  熊刚
Adobe PDF(1647Kb)  |  收藏  |  浏览/下载：266/75  |  提交时间：2022/04/08
深度学习, 模型剪枝 , 卷积神经网络 , 稀疏约束, 模型压缩  
A Semi-supervised End-to-end Framework for Transportation Mode Detection by Using GPS-enabled Sensing Devices 期刊论文
IEEE Internet of Things Journal, 2022, 卷号: 9, 期号: 10, 页码: 7842-7852
作者:  Zhishuai Li;  Gang Xiong;  Zebing Wei;  YIsheng Lv;  Noreen Anwar;  Fei-Yue Wang
Adobe PDF(2754Kb)  |  收藏  |  浏览/下载：234/72  |  提交时间：2022/04/08
Transportation mode detection , Semi-supervised learning, Human mobility , GPS trajectory.  
A Feedback-Based Print Quality Improving Strategy for FDM 3D Printing: An Optimal Design Approach 期刊论文
The International Journal of Advanced Manufacturing Technology, 2022, 期号: 2022, 页码: 1-15
作者:  Tamir, Tariku Sinshaw;  Xiong, Gang;  Fang,Qihang;  Dong,Xisong;  Shen,Zhen;  Wang,Fei-Yue
Adobe PDF(2116Kb)  |  收藏  |  浏览/下载：265/70  |  提交时间：2022/04/07
Industry4.0, 3D Printing, Print Quality, Error Causing Parameters, Deformations, Fuzzy Inference System  
Trip Purposes Mining From Mobile Signaling Data 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2021, 卷号: 99, 期号: 99, 页码: 13
作者:  Li, Zhishuai;  Xiong, Gang;  Wei, Zebing;  Zhang, Yu;  Zheng, Meng;  Liu, Xiaoli;  Tarkoma, Sasu;  Huang, Min;  Lv, Yisheng;  Wu, Chuheng
Adobe PDF(3962Kb)  |  收藏  |  浏览/下载：456/78  |  提交时间：2022/01/27
Cellular networks  Trajectory  Semantics  Unsupervised learning  Supervised learning  Resource management  Public transportation  Trip purpose inference  cellular network data  latent Dirichlet allocation  travel behavior  big data  
3D-RVP: A method for 3D object reconstruction from a single depth view using voxel and point 期刊论文
NEUROCOMPUTING, 2021, 卷号: 430, 期号: 2021, 页码: 94-103
作者:  Zhao, Meihua;  Xiong, Gang;  Zhou, MengChu;  Shen, Zhen;  Wang, Fei-Yue
Adobe PDF(1476Kb)  |  收藏  |  浏览/下载：318/41  |  提交时间：2021/03/29
3D object reconstruction  Encoder-decoder network  Machine learning  Point prediction network  
Parallel Transportation Systems: Toward IoT-Enabled Smart Urban Traffic Control and Management 期刊论文
IEEE Transactions on Intelligent Transportation Systems, 2020, 卷号: 21, 期号: 10, 页码: 4063 - 4071
作者:  Fenghua Zhu;  Yisheng Lv;  Yuanyuan Chen;  Xiao Wang;  Gang Xiong;  Fei-Yue Wang
浏览  |  Adobe PDF(2879Kb)  |  收藏  |  浏览/下载：476/234  |  提交时间：2020/10/15
Intelligent transportation systems  
A Multi-Stream Feature Fusion Approach for Traffic Prediction 期刊论文
IEEE Transactions on Intelligent Transportation Systems, 2022, 卷号: 23, 期号: 2, 页码: 1456-1466
作者:  Zhishuai Li;  Gang Xiong;  Yonglin Tian;  Yisheng Lv;  Yuanyuan Chen;  Pan Hui;  Xiang Su
Adobe PDF(3248Kb)  |  收藏  |  浏览/下载：398/71  |  提交时间：2020/10/15
Traffic prediction, graph convolutional neural network, deep learning, multi-stream