Going Small with Efficient Models for Large Problems
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Aaditeshwar Seth
May 6, 2026, 1:02:04 PM (5 days ago) May 6
to learning, ac...@googlegroups.com, CoRE stack: NRM, CoRE Stack
This is an excellent approach, to think of common tasks for which specific small models can be trained. This one is for a very common task to find the geometry of a district or some map element. What other similar tasks can you think of that you end up doing on QGIS, GEE, etc.? One is certainly clipping layers to a boundary or generating stats of % area under various classes. The blog makes it sound easy to do this, by querying a dataset repository like the GEE catalogs or STAC atlas to identify datasets, and then use various libraries to do the job. Any takers for this, please discuss on the dev call and kick it off!
Adi
Co-founder, Gram Vaani; Co-founder, CoRE Stack
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