Advances in deep learning-driven photo identification and meta analysis of cetaceans in large data repositories

Photo-identification of cetaceans remains a labor-intensive task, requiring expert annotation of long-tailed image datasets in which most individuals are rarely encountered. We present a scalable, end-to-end framework that automates this process using lightweight deep learning models optimized for r...

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Veröffentlicht in:	Ecological informatics Jg. 91; S. 103396
Hauptverfasser:	Barnhill, Alexander, Towers, Jared R., Shaw, Tasli J.H., Arias, Magdalena, Bécares, Adrián, Doniol-Valcroze, Thomas, von Fersen, Lorenzo, Genoves, Rodrigo, Rörup, Tim, Sutton, Gary J., Thornton, Sheila, Weiss, Michael, Maier, Andreas, Nöth, Elmar, Bergler, Christian
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.11.2025 Elsevier
Schlagworte:	Data curation Deep learning Marine conservation Photo identification Resource efficient machine learning Deep learning Data curation Photo identification Resource efficient machine learning Marine conservation
ISSN:	1574-9541
Online-Zugang:	Volltext
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