STULL: Unbiased Online Sampling for Visual Exploration of Large Spatiotemporal Data-Reference-Cited by-同舟云学术

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STULL: Unbiased Online Sampling for Visual Exploration of Large Spatiotemporal Data

Published:2020-10 Issue: Volume: Page:
ISSN:
Container-title:2020 IEEE Conference on Visual Analytics Science and Technology (VAST)
language:
Short-container-title:

Author:

Wang Guizhen,Guo Jingjing,Tang Mingjie,Queiroz Neto Jose Florencio de,Yau Calvin,Daghistani Anas,Karimzadeh Morteza,Aref Walid G.,Ebert David S.

Funder

National Science Foundation

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9308302/9308614/09308629.pdf?arnumber=9308629

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. User-centered visual explorer of in-process comparison in spatiotemporal space;Journal of Visualization;2022-11-09

2. A survey of urban visual analytics: Advances and future directions;Computational Visual Media;2022-10-18

3. DDLVis: Real-time Visual Query of Spatiotemporal Data Distribution via Density Dictionary Learning;IEEE Transactions on Visualization and Computer Graphics;2022-01

4. Visual abstraction of large-scale geographical point data with credible spatial interpolation;Journal of Visualization;2021-08-19

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