GeoAI in resource-constrained environments
Fuente:
arXiv
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| Autori principali: | , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866913486884306944 |
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| author | Böhlen, Marc Sughiarta, Gede Kurnianingsih, Atiek Gopaladinne, Srikar Reddy Shrivastava, Sujay Gorla, Hemanth Kumar Reddy |
| author_facet | Böhlen, Marc Sughiarta, Gede Kurnianingsih, Atiek Gopaladinne, Srikar Reddy Shrivastava, Sujay Gorla, Hemanth Kumar Reddy |
| contents | This paper describes spatially aware Artificial Intelligence, GeoAI, tailored for small organizations such as NGOs in resource constrained contexts where access to large datasets, expensive compute infrastructure and AI expertise may be restricted. We furthermore consider future scenarios in which resource-intensive, large geospatial models may homogenize the representation of complex landscapes, and suggest strategies to prepare for this condition. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_17361 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | GeoAI in resource-constrained environments Böhlen, Marc Sughiarta, Gede Kurnianingsih, Atiek Gopaladinne, Srikar Reddy Shrivastava, Sujay Gorla, Hemanth Kumar Reddy Computers and Society This paper describes spatially aware Artificial Intelligence, GeoAI, tailored for small organizations such as NGOs in resource constrained contexts where access to large datasets, expensive compute infrastructure and AI expertise may be restricted. We furthermore consider future scenarios in which resource-intensive, large geospatial models may homogenize the representation of complex landscapes, and suggest strategies to prepare for this condition. |
| title | GeoAI in resource-constrained environments |
| topic | Computers and Society |
| url | https://arxiv.org/abs/2408.17361 |