Research on trajectory compression algorithm based on deep learning-Reference-Cited by-同舟云学术

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Research on trajectory compression algorithm based on deep learning

Published:2024-04-19 Issue: Volume:16 Page:625-630
ISSN:
Container-title:2024 5th International Conference on Computer Vision, Image and Deep Learning (CVIDL)
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Author:

Zhao Xinhui¹,Yang Liu²,Liu Heng³

Affiliation:

1. Southwest Jiaotong University,Information Coding Tangshan Research Institute,Tangshan,Hebei,China,063002

2. Southwest Jiaotong University,School of Information Science and Technology,Chengdu,Sichuan,China,611756

3. Southwest Jiaotong University,Information Coding & Transmission (ICT) Key Laboratory of Sichuan Province,Chengdu,Si Chuan,China,611756

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10603448/10603453/10603753.pdf?arnumber=10603753

Reference10 articles.

1. Reflection Essay: Algorithms for the Reduction of the Number of Points Required to Represent a Digitized Line or its Caricature

2. A trajectory clustering method based on Douglas-Peucker compression and density for marine traffic pattern recognition

3. Spatio-temporal compression of trajectories in road networks

4. Semantic trajectory compression: Representing urban movement in a nutshell

5. Semi-Supervised Classification with Graph Convolutional Networks[J];Kipf

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