biasvariancelabs/aitlas-arena
An open-source benchmark framework for evaluating state-of-the-art deep learning approaches for image classification in Earth Observation (EO)
This project helps researchers and practitioners evaluate and compare different deep learning models for classifying satellite and aerial imagery. It takes various Earth Observation image datasets as input and provides comprehensive performance benchmarks for over 500 pre-trained models. The primary users are remote sensing scientists, environmental analysts, and geospatial engineers developing image classification solutions.
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Use this if you need to understand which deep learning models perform best for specific image classification tasks in Earth Observation.
Not ideal if you are looking for an off-the-shelf application to classify your own satellite images without delving into model evaluation.
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MIT
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Apr 19, 2024
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