66 citations · 74 across the 5 of their papers we have counts for
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cs.AI2024★ 2 cited
Self-Supervised Representation Learning for Geospatial Objects: A Survey
Yile Chen, Weiming Huang, Kaiqi Zhao +2
The proliferation of various data sources in urban and territorial environments has significantly facilitated the development of geospatial artificial intelligence (GeoAI) across a…
cs.AI2023★ 66 cited
On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligence
Gengchen Mai, Weiming Huang, Jin Sun +11
Large pre-trained models, also known as foundation models (FMs), are trained in a task-agnostic manner on large-scale data and can be adapted to a wide range of downstream tasks by…