中国科学院计算技术研究所机构知识库

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限定条件	资助项目：National Natural Science Foundation of China[61872046]    资助项目：Open Project of the Beijing Key Laboratory of Mobile Computing and Pervasive Device    资助项目：Science and Technology Plan Project of Inner Mongolia Autonomous Regio[2019GG328]

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
	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
	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
	RL-AKF: An Adaptive Kalman Filter Navigation Algorithm Based on Reinforcement Learning for Ground Vehicles 期刊论文 REMOTE SENSING, 2020, 卷号: 12, 期号: 11, 页码: 25 作者:  Gao, Xile;  Luo, Haiyong;  Ning, Bokun;  Zhao, Fang;  Bao, Linfeng;  Gong, Yilin;  Xiao, Yimin;  Jiang, Jinguang 收藏  |  浏览/下载：57/0  |  提交时间：2020/12/10 integrated navigation  Kalman filter  process noise covariance estimation  reinforcement learning  deep deterministic policy gradient
	Adaptive Kalman filtering-based pedestrian navigation algorithm for smartphones 期刊论文 INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS, 2020, 卷号: 17, 期号: 3, 页码: 14 作者:  Yu, Chen;  Luo, Haiyong;  Fang, Zhao;  Qu, Wang;  Shao, Wenhua 收藏  |  浏览/下载：47/0  |  提交时间：2020/12/10 Pedestrian navigation  error model system  inertial sensors integration  magnetic field  heading estimation