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LifeCLEF 2024 Teaser: Challenges on Species Distribution Prediction and Identification., , , , , , , , , и 14 other автор(ы). ECIR (6), том 14613 из Lecture Notes in Computer Science, стр. 19-27. Springer, (2024)Evaluation of Deep Species Distribution Models using Environment and Co-occurrences., , , и . CoRR, (2019)The GeoLifeCLEF 2020 Dataset., , , , , , , , и . CoRR, (2020)LifeCLEF 2020 Teaser: Biodiversity Identification and Prediction Challenges., , , , , , , , , и 6 other автор(ы). ECIR (2), том 12036 из Lecture Notes in Computer Science, стр. 542-549. Springer, (2020)LifeCLEF 2023 Teaser: Species Identification and Prediction Challenges., , , , , , , , , и 12 other автор(ы). ECIR (3), том 13982 из Lecture Notes in Computer Science, стр. 568-576. Springer, (2023)Overview of LifeCLEF 2023: Evaluation of AI Models for the Identification and Prediction of Birds, Plants, Snakes and Fungi., , , , , , , , , и 12 other автор(ы). CLEF, том 14163 из Lecture Notes in Computer Science, стр. 416-439. Springer, (2023)Overview of GeoLifeCLEF 2023: Species Composition Prediction with High Spatial Resolution at Continental Scale Using Remote Sensing., , , , , , , , и . CLEF (Working Notes), том 3497 из CEUR Workshop Proceedings, стр. 1954-1971. CEUR-WS.org, (2023)Overview of GeoLifeCLEF 2018: Location-based Species Recommendation., , , , и . CLEF (Working Notes), том 2125 из CEUR Workshop Proceedings, CEUR-WS.org, (2018)Convolutional neural networks improve species distribution modelling by capturing the spatial structure of the environment., , , , , и . PLoS Comput. Biol., (2021)LifeCLEF 2019: Biodiversity Identification and Prediction Challenges., , , , , , , , , и 3 other автор(ы). ECIR (2), том 11438 из Lecture Notes in Computer Science, стр. 275-282. Springer, (2019)