A deep-learning based approach to detect and classify animals flying near wind turbines using thermal surveillance cameras and open-source software

Yarbrough, J.; Cuntiz, I.; Schipper, J.; Lawson, M.; Straw, B.; Hein, C.; Cryan, P.

doi:10.1101/2023.02.26.530152

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bioRxiv · 10.1101/2023.02.26.530152

A deep-learning based approach to detect and classify animals flying near wind turbines using thermal surveillance cameras and open-source software

Yarbrough, J.·Cuntiz, I.·Schipper, J.·Lawson, M.·Straw, B.·Hein, C.·Cryan, P.

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Abstract

The authors have withdrawn their manuscript because it was distributed without the proper approvals from the United States Geological Survey. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.

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Yarbrough, J., Cuntiz, I., Schipper, J., Lawson, M., Straw, B., Hein, C., Cryan, P.. 2023-02-27. A deep-learning based approach to detect and classify animals flying near wind turbines using thermal surveillance cameras and open-source software. https://doi.org/10.1101/2023.02.26.530152

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