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pro vyhledávání: '"KELLENBERGER"'
Autor:
van Tiel, Nina, Zbinden, Robin, Dalsasso, Emanuele, Kellenberger, Benjamin, Pellissier, Loïc, Tuia, Devis
Species distribution models (SDMs) aim to predict the distribution of species by relating occurrence data with environmental variables. Recent applications of deep learning to SDMs have enabled new avenues, specifically the inclusion of spatial data
Externí odkaz:
http://arxiv.org/abs/2411.04016
Automated wildlife surveys based on drone imagery and object detection technology are a powerful and increasingly popular tool in conservation biology. Most detectors require training images with annotated bounding boxes, which are tedious, expensive
Externí odkaz:
http://arxiv.org/abs/2410.11741
Publikováno v:
Ecological Informatics, Volume 81, 2024, 102623
Species distribution modeling is a highly versatile tool for understanding the intricate relationship between environmental conditions and species occurrences. However, the available data often lacks information on confirmed species absence and is li
Externí odkaz:
http://arxiv.org/abs/2401.02989