Overview of SnakeCLEF 2022: Automated Snake Species Identification on a Global Scale

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dc.contributor.authorPicek, Lukáš
dc.contributor.authorHrúz, Marek
dc.contributor.authorDurso, Andrew M.
dc.contributor.authorBolon, Isabelle
dc.date.accessioned2023-02-13T11:00:21Z
dc.date.available2023-02-13T11:00:21Z
dc.date.issued2022
dc.description.abstract-translatedThe main goal of the third year of the SnakeCLEF challenge was to provide an evaluation platform that helps track the performance of AI-driven methods for snake species recognition systems on a global scale and allows direct comparison with human experts. We ran two challenges separately for humans — experts and novices — and AI methods in order to lay the groundwork for future comparison between human and machine-based snake species identification. We have provided 187,129 snake observations with 318,532 photographs — 270,251 for training and 48,281 for testing — of 1,572 snake species collected in 208 countries. The human performance evaluation was conducted on a tailored subset with 150 images derived from the full test set. We report (i) a description of the provided data, (ii) evaluation methodology and principles, (iii) an overview of the methods submitted by the participating teams, and (iv) a discussion of the obtained results. © 2022 Copyright for this paper by its authors.en
dc.format13 s.cs
dc.format.mimetypeapplication/pdf
dc.identifier.citationPICEK, L. HRÚZ, M. DURSO, AM. BOLON, I. Overview of SnakeCLEF 2022: Automated Snake Species Identification on a Global Scale. In Proceedings of the Working Notes of CLEF 2022 - Conference and Labs of the Evaluation Forum. Bologna: CEUR-WS, 2022. s. 1957-1969. ISBN: neuvedeno , ISSN: 1613-0073cs
dc.identifier.isbnneuvedeno
dc.identifier.issn1613-0073
dc.identifier.obd43937113
dc.identifier.uri2-s2.0-85136952391
dc.identifier.urihttp://hdl.handle.net/11025/51465
dc.language.isoenen
dc.project.IDSS05010008/Detekce, identifikace a monitoring živočichů pokročilými metodami počítačového viděnícs
dc.project.IDSGS-2022-017/Inteligentní metody strojového vnímání a porozumění 5cs
dc.project.IDLM2018101/LINDAT/CLARIAH-CZ – Digitální výzkumná infrastruktura pro jazykové technologie, umění a humanitní vědycs
dc.publisherCEUR-WSen
dc.relation.ispartofseriesProceedings of the Working Notes of CLEF 2022 - Conference and Labs of the Evaluation Forumen
dc.rights© authorsen
dc.rights.accessopenAccessen
dc.subject.translatedbenchmarken
dc.subject.translatedbiodiversityen
dc.subject.translatedclassificationen
dc.subject.translatedcomputer visionen
dc.subject.translatedepidemiologyen
dc.subject.translatedfine grained visual categorizationen
dc.subject.translatedglobal healthen
dc.subject.translatedLifeCLEFen
dc.subject.translatedmachine learningen
dc.subject.translatedreptileen
dc.subject.translatedsnakeen
dc.subject.translatedsnake biteen
dc.subject.translatedSnakeCLEFen
dc.subject.translatedspecies identificationen
dc.titleOverview of SnakeCLEF 2022: Automated Snake Species Identification on a Global Scaleen
dc.typekonferenční příspěvekcs
dc.typeConferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen

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