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Participation of LIRMM / Inria to the GeoLifeCLEF 2020 Challenge.

, , , , and . CLEF (Working Notes), volume 2696 of CEUR Workshop Proceedings, CEUR-WS.org, (2020)

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Modelling Species Distributions with Deep Learning to Predict Plant Extinction Risk and Assess Climate Change Impacts., , , , and . CoRR, (2024)AI-based Mapping of the Conservation Status of Orchid Assemblages at Global Scale., , , , and . CoRR, (2024)A Deep Learning Approach to Species Distribution Modelling., , , , and . Multimedia Tools and Applications for Environmental & Biodiversity Informatics, Springer, (2018)Participation of LIRMM / Inria to the GeoLifeCLEF 2020 Challenge., , , , and . CLEF (Working Notes), volume 2696 of CEUR Workshop Proceedings, CEUR-WS.org, (2020)Statistical ecology comes of age, , , , , , , , , and 14 other author(s). Biology Letters, 10 (12): 20140698 (December 2014)Convolutional neural networks improve species distribution modelling by capturing the spatial structure of the environment., , , , , and . PLoS Comput. Biol., (2021)How Do Deep Convolutional SDM Trained on Satellite Images Unravel Vegetation Ecology?, , , , and . ICPR Workshops (6), volume 12666 of Lecture Notes in Computer Science, page 148-158. Springer, (2020)Overview of GeoLifeCLEF 2018: Location-based Species Recommendation., , , , and . CLEF (Working Notes), volume 2125 of CEUR Workshop Proceedings, CEUR-WS.org, (2018)