A general deep learning model for bird detection in high‐resolution airborne imagery

Advances in artificial intelligence for computer vision hold great promise for increasing the scales at which ecological systems can be studied. The distribution and behavior of individuals is central to ecology, and computer vision using deep neural networks can learn to detect individual objects i...

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Veröffentlicht in:	Ecological applications 2022-12, Vol.32 (8), p.e2694-n/a
Hauptverfasser:	Weinstein, Ben G., Garner, Lindsey, Saccomanno, Vienna R., Steinkraus, Ashley, Ortega, Andrew, Brush, Kristen, Yenni, Glenda, McKellar, Ann E., Converse, Rowan, Lippitt, Christopher D., Wegmann, Alex, Holmes, Nick D., Edney, Alice J., Hart, Tom, Jessopp, Mark J., Clarke, Rohan H., Marchowski, Dominik, Senyondo, Henry, Dotson, Ryan, White, Ethan P., Frederick, Peter, Ernest, S. K. Morgan
Format:	Artikel
Sprache:	eng
Schlagworte:	airborne monitoring Animals Annotations Artificial Intelligence Artificial neural networks bird detection Birds Computer applications Computer vision Data collection Deep Learning Ecological monitoring Ecosystem Humans Image resolution Machine learning Neural networks Neural Networks, Computer Object recognition Recall Training unoccupied aerial vehicle
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