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README.md

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+license: mit
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+# Bird Detection in RGB Airborne Imagery
+The model was initially described in [Ecological Applications](https://esajournals.onlinelibrary.wiley.com/doi/abs/10.1002/eap.2694). From the abstract
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+ Using over 250,000 annotations from 13 projects from around the world, we develop a general bird detection model that achieves over 65% recall and 50% precision on novel aerial data without any local training despite differences in species, habitat, and imaging methodology. Fine-tuning this model with only 1000 local annotations increases these values to an average of 84% recall and 69% precision by building on the general features learned from other data sources. 
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