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Found 4 papers, 0 papers with code
Can SAM recognize crops? Quantifying the zero-shot performance of a semantic segmentation foundation model on generating crop-type maps using satellite imagery for precision agriculture
This paper attempts to highlight a use-case of state-of-the-art image segmentation models like SAM for crop-type mapping and related specific needs of the agriculture industry, offering a potential avenue for automatic, efficient, and cost-effective data products for precision agriculture practices.
Object Delineation in Satellite Images
Machine learning is being widely applied to analyze satellite data with problems such as classification and feature detection.
Uncertainty Aware Wildfire Management
A major problem in using data-driven models to combat wildfires is the lack of comprehensive data sources that relate fires with relevant covariates.
DeepSampling: Selectivity Estimation with Predicted Error and Response Time
The rapid growth of spatial data urges the research community to find efficient processing techniques for interactive queries on large volumes of data.
