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Akademický článek

Do you get what you see? Insights of using mAP to select architectures of pretrained neural networks for automated aerial animal detection.

Autor: Mael Moreni, Jerome Theau, Samuel Foucher

Publikováno v: PLoS ONE, Vol 18, Iss 4, p e0284449 (2023)

The vast amount of images generated by aerial imagery in the context of regular wildlife surveys nowadays require automatic processing tools. At the top of the mountain of different methods to automatically detect objects in images reigns deep learni

Externí odkaz: https://doaj.org/article/4e41e5e252f2457f9619d77524116b3c

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Train Fast While Reducing False Positives: Improving Animal Classification Performance Using Convolutional Neural Networks

Autor: Samuel Foucher, Jérôme Théau, Mael Moreni

Publikováno v: Geomatics
Volume 1
Issue 1
Pages 4-49

The combination of unmanned aerial vehicles (UAV) with deep learning models has the capacity to replace manned aircrafts for wildlife surveys. However, the scarcity of animals in the wild often leads to highly unbalanced, large datasets for which eve

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c57764483a88fa13af9a3e4a74d4820d
https://doi.org/10.3390/geomatics1010004

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