#terrainmapping - Livello Segreto

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Greg Cocks @GregCocks@techhub.social

Segment Anything Model Can Not Segment Anything - Assessing AI Foundation Model’s Generalizability In Permafrost Mapping
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https://doi.org/10.3390/rs16050797 <-- shared paper
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#GIS #spatial #mapping #remotesensing #foundationmodel #AI #artificialintelligence #zeroshot #segmentation #GeoAI #spatialanalysis #LargeLanguageModel #LLM #SAM #performance #metrics #permafrost #visionmodel #icewedge #Arctic #warming #climatechange #thawslumps #landform #terrainmapping #EuroCrops #agriculture

photo - permafrost on a steep slope, with an ice wedge, Arctic Alaska

schematic / work flow - Architecture of SAM (left of the dashed line) and CLIP (right of the dashed line) and their combined workflow for instance segmentation

maps/images - Results from knowledge-embedded learning with SAM. The results are those after fine-tuning. The images are the same as those in [other figure.]

maps/images - Results of zero-shot learning with the integrated SAM+CLIP model. Mask colors in red and blue represent ground-truth labels and model prediction respectively. The last column displays the final result, and the second-to-last column presents the intermediate results from SAM, which are used as input for CLIP.

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