您当前的位置：
首页 >
文章列表页 >
Trajectory k nearest neighbor query method based on sparse multi-head attention
更新时间：2025-05-26

    • Trajectory k nearest neighbor query method based on sparse multi-head attention

    • “In the field of spatiotemporal data, experts have proposed a trajectory encoder based on sparse multi head self attention mechanism, which provides an efficient solution for large-scale trajectory data queries.”
    • Journal of Jilin University(Engineering and Technology Edition)   Vol. 54, Issue 6, Pages: 1756-1766(2024)
    • 作者机构：

      哈尔滨理工大学 计算机科学与技术学院，哈尔滨 150080

    • DOI：10.13229/j.cnki.jdxbgxb.20220865    

      CLC： TP311

    • Received：07 July 2022，

      Published：01 June 2024

    移动端阅览

  • ZHANG Li-ping,LIU Bin-yu,LI Song,et al.Trajectory k nearest neighbor query method based on sparse multi-head attention[J].Journal of Jilin University(Engineering and Technology Edition),2024,54(06):1756-1766. DOI： 10.13229/j.cnki.jdxbgxb.20220865.

  •  
  •  

0

Views

9

下载量

0

CSCD

Alert me when the article has been cited
提交
Tools
Download
Export Citation
Share
Add to favorites
Add to my album

Related Articles

A method for generating proposals of medical image based on prior knowledge optimization
Deep learning-based method for ribonucleic acid secondary structure prediction
Object extraction of yellow catfish based on RGHS image enhancement and improved YOLOv5 network
Video saliency prediction with collective spatio-temporal attention
Deep-learning-based two-stage approach for real-time explicit topology optimization

Related Author

XU Huan
LIU Quan-le
ZHAO Meng-xue
CHE Xiang-jiu
ZANG Zi-nan
LIU Zhen
LIU Yuan-ning
ZHANG Hao

Related Institution

College of Computer Science and Technology， Jilin University
Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education ， Jilin University
Graduate School of Engineering，Nagasaki Institute of Applied Science
College of Engineering， Huazhong Agricultural University
Key Laboratory of Aquaculture Facilities Engineering， Ministry of Agriculture and Rural Affairs
0