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DeepFaune New England: A species classification model for trail camera images in northeastern North America

Laurence A. Clarfeld·Katherine D. Gieder·Angela K. Fuller·Zhongqi Miao·Alexej P.K. Sirén·Shevenell M. Webb·Toni Lyn Morelli·Jillian R. Kilborn·Catherine B. Callahan·Leighlan S. Prout·Rachel Cliché·Riley K. Patry·Christopher Bernier·Susan Staats·Therese M. Donovan
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Abstract

The DeepFaune New England model classifies wildlife species in trail camera images, identifying 24 taxa from northeastern North America with high (97%) accuracy. The model was adapted from the DeepFaune model for identifying European wildlife, demonstrating the practicality of transfer learning across continents. The majority of training data is openly licensed, and the model itself is open source, enabling easy integration into camera trapping workflows. The open source software is available at ( https://code.usgs.gov/vtcfwru/deepfaune-new-england ), and has been further integrated into the PyTorch-Wildlife framework.

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Ecology and EvolutionArticle
90° N90° S · 180° W ← longitude → 180° E
Source-reported bounding extent: 40.33015889138204° to 47.5296422169192° latitude; -73.75929702181658° to -66.96355818373794° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

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BibTeXRIS

Laurence A. Clarfeld, Katherine D. Gieder, Angela K. Fuller, Zhongqi Miao, Alexej P.K. Sirén, Shevenell M. Webb, Toni Lyn Morelli, Jillian R. Kilborn, Catherine B. Callahan, Leighlan S. Prout, Rachel Cliché, Riley K. Patry, Christopher Bernier, Susan Staats, Therese M. Donovan. 2025-11-14. DeepFaune New England: A species classification model for trail camera images in northeastern North America. https://doi.org/10.1002/ece3.72174

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