Learning Universal Trajectory Representation via a Siamese Geography-Aware Transformer
With the development of location-based services and data collection equipment, the volume of trajectory data has been growing at a phenomenal rate. Raw trajectory data come in the form of sequences of “coordinate-time-attribute” triplets, which require complicated manual processing before they can b...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-02-01
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| Series: | ISPRS International Journal of Geo-Information |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2220-9964/13/3/64 |