Tools for Test & Evaluation on Incompletely-Labeled Satellite Imagery Datasets
This grant opportunity involves developing tools for analyzing the performance of AI/ML models on satellite imagery with label noise across various environmental conditions.
Phase I: Create a basic software to estimate AI/ML performance on satellite imagery tasks, resilient to noisy or missing data, applicable to different datasets and architectures. Deliver software an…
Develop tooling for rapid performance analysis of diverse AI/ML models on overhead imagery datasets with label noise, over wide ranges of environmental conditions.
Phase I
Demonstrate a basic software package for the estimation of AI/ML model performance on computer vison detecto…
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