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dc.contributor.authorJoly, Alexis
dc.contributor.authorGoëau, Hervé
dc.contributor.authorKahl, Stefan
dc.contributor.authorPicek, Lukáš
dc.contributor.authorLorieul, Titouan
dc.contributor.authorCole, Elijah
dc.contributor.authorDeneu, Benjamin
dc.contributor.authorServajean, Maximillien
dc.contributor.authorDurso, Andrew M.
dc.contributor.authorBolon, Isabelle
dc.contributor.authorGlotin, Hervé
dc.contributor.authorPlanqué, Robert
dc.contributor.authorVellinga, Willem-Pier
dc.contributor.authorKlinck, Holger
dc.contributor.authorDenton, Tom
dc.contributor.authorEggel, Ivan
dc.contributor.authorBonnet, Pierre
dc.contributor.authorMüller, Henning
dc.contributor.authorŠulc, Milan
dc.date.accessioned2023-01-16T11:00:17Z-
dc.date.available2023-01-16T11:00:17Z-
dc.date.issued2022
dc.identifier.citationJOLY, A. GOËAU, H. KAHL, S. PICEK, L. LORIEUL, T. COLE, E. DENEU, B. SERVAJEAN, M. DURSO, AM. BOLON, I. GLOTIN, H. PLANQUÉ, R. VELLINGA, W. KLINCK, H. DENTON, T. EGGEL, I. BONNET, P. MÜLLER, H. ŠULC, M. LifeCLEF 2022 Teaser: An Evaluation of Machine-Learning Based Species Identification and Species Distribution Prediction. In Advances in Information Retrieval Book : 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10–14, 2022, Proceedings, Part II. Cham: Springer, 2022. s. 390-399. ISBN: 978-3-030-99738-0 , ISSN: 0302-9743cs
dc.identifier.isbn978-3-030-99738-0
dc.identifier.issn0302-9743
dc.identifier.uri2-s2.0-85128722595
dc.identifier.urihttp://hdl.handle.net/11025/50933
dc.format10 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherSpringeren
dc.relation.ispartofseriesAdvances in Information Retrieval Book : 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10–14, 2022, Proceedings, Part IIen
dc.rightsPlný text je přístupný v rámci univerzity přihlášeným uživatelům.cs
dc.rights© The Author(s), under exclusive license to Springer Nature Switzerland AGen
dc.titleLifeCLEF 2022 Teaser: An Evaluation of Machine-Learning Based Species Identification and Species Distribution Predictionen
dc.typekonferenční příspěvekcs
dc.typeConferenceObjecten
dc.rights.accessrestrictedAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedBuilding accurate knowledge of the identity, the geographic distribution and the evolution of species is essential for the sustainable development of humanity, as well as for biodiversity conservation. However, the difficulty of identifying plants, animals and fungi is hindering the aggregation of new data and knowledge. Identifying and naming living organisms is almost impossible for the general public and is often difficult even for professionals and naturalists. Bridging this gap is a key step towards enabling effective biodiversity monitoring systems. The LifeCLEF campaign, presented in this paper, has been promoting and evaluating advances in this domain since 2011. The 2022 edition proposes five data-oriented challenges related to the identification and prediction of biodiversity: (i) PlantCLEF: very large-scale plant identification, (ii) BirdCLEF: bird species recognition in audio soundscapes, (iii) GeoLifeCLEF: remote sensing based prediction of species, (iv) SnakeCLEF: Snake Species Identification in Medically Important scenarios, and (v) FungiCLEF: Fungi recognition from images and metadata.en
dc.subject.translatedAIen
dc.subject.translatedBiodiversityen
dc.subject.translatedBird identificationen
dc.subject.translatedMachine learningen
dc.subject.translatedPlant identificationen
dc.subject.translatedSnake identificationen
dc.subject.translatedSpecies distribution modelen
dc.subject.translatedSpecies identificationen
dc.subject.translatedSpecies predictionen
dc.identifier.doi10.1007/978-3-030-99739-7_49
dc.type.statusPeer-revieweden
dc.identifier.document-number787788000049
dc.identifier.obd43937001
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Konferenční příspěvky / Conference Papers (KKY)
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