A graph autoencoder network to measure the geometric similarity of drainage networks in scaling transformation
Similarity measurement has been a prevailing research topic in geographic information science. Geometric similarity measurement in scaling transformation (GSM_ST) is critical to ensure spatial data quality while balancing detailed information with distinctive features. However, GSM_ST is an uncertai...
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Main Authors: | , , , , |
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Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2024
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/173624 |
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Institution: | Nanyang Technological University |
Language: | English |