中国科学院计算技术研究所机构知识库

浏览/检索结果: 共5条，第1-5条

帮助

限定条件	资助项目：National Natural Science Foundation of China[61872046]

已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择期刊影响因子升序期刊影响因子降序发表日期升序发表日期降序提交时间升序提交时间降序作者升序作者降序WOS被引频次升序WOS被引频次降序题名升序题名降序
	Learning All Dynamics: Traffic Forecasting via Locality-Aware Spatio-Temporal Joint Transformer 期刊论文 IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 页码: 14 作者:  Fang, Yuchen;  Zhao, Fang;  Qin, Yanjun;  Luo, Haiyong;  Wang, Chenxing 收藏  |  浏览/下载：29/0  |  提交时间：2022/12/07 Forecasting  Correlation  Convolution  Roads  Transformers  Predictive models  Task analysis  Traffic forecasting  spatio-temporal joint transformer  diffusion convolution network
	Fine-Grained Trajectory-Based Travel Time Estimation for Multi-City Scenarios Based on Deep Meta-Learning 期刊论文 IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 页码: 13 作者:  Wang, Chenxing;  Zhao, Fang;  Zhang, Haichao;  Luo, Haiyong;  Qin, Yanjun;  Fang, Yuchen 收藏  |  浏览/下载：19/0  |  提交时间：2022/12/07 Estimation  Trajectory  Task analysis  Urban areas  Roads  Data models  Global Positioning System  Spatial-temporal data mining  travel time estimation  meta learning  deep learning
	Particle Filter Reinforcement via Context-Sensing for Smartphone-Based Pedestrian Dead Reckoning 期刊论文 IEEE COMMUNICATIONS LETTERS, 2021, 卷号: 25, 期号: 9, 页码: 3144-3148 作者:  Shao, Wenhua;  Zhao, Fang;  Luo, Haiyong;  Tian, Hui;  Li, Jiaxin;  Crivello, Antonino 收藏  |  浏览/下载：41/0  |  提交时间：2021/12/01 Particle filters  Neural networks  Reinforcement learning  Mathematical model  Particle measurements  Estimation  Atmospheric measurements  Indoor location tracking  particle filter  pedestrian dead reckoning  reinforcement learning  smartphone-based navigation
	ADST: Forecasting Metro Flow Using Attention-Based Deep Spatial-Temporal Networks with Multi-Task Learning 期刊论文 SENSORS, 2020, 卷号: 20, 期号: 16, 页码: 23 作者:  Jia, Hongwei;  Luo, Haiyong;  Wang, Hao;  Zhao, Fang;  Ke, Qixue;  Wu, Mingyao;  Zhao, Yunyun 收藏  |  浏览/下载：51/0  |  提交时间：2020/12/10 forecasting passenger flow  spatiotemporal networks  multi-task learning  attention mechanism  spatiotemporal dependency
	Toward improving indoor magnetic field-based positioning system using pedestrian motion models 期刊论文 INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS, 2018, 卷号: 14, 期号: 9, 页码: 20 作者:  Shao, Wenhua;  Luo, Haiyong;  Zhao, Fang;  Crivello, Antonino 收藏  |  浏览/下载：83/0  |  提交时间：2019/08/16 Indoor location-based services  pedestrian motion model  magnetic field positioning  attitude detection  indoor positioning