Overview of LifeCLEF 2023: evaluation of AI models for the identification and prediction of birds, plants, snakes and fungi - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2023

Overview of LifeCLEF 2023: evaluation of AI models for the identification and prediction of birds, plants, snakes and fungi

Abstract

Biodiversity monitoring through AI approaches is essential, as it enables the efficient analysis of vast amounts of data, providing comprehensive insights into species distribution and ecosystem health and aiding in informed conservation decisions. Species identification based on images and sounds, in particular, is invaluable for facilitating biodiversity monitoring efforts and enabling prompt conservation actions to protect threatened and endangered species. The LifeCLEF virtual lab has been promoting and evaluating advances in this domain since 2011. The 2023 edition proposes five data-oriented challenges related to the identification and prediction of biodiversity: (i) BirdCLEF: bird species recognition in long-term audio recordings (soundscapes), (ii) SnakeCLEF: snake identification in medically important scenarios, (iii) PlantCLEF: very largescale plant identification, (iv) FungiCLEF: fungi recognition beyond 0-1 cost, and (v) GeoLifeCLEF: remote sensing-based prediction of species. This paper overviews the motivation, methodology, and main outcomes of that five challenges.
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Dates and versions

hal-04322219 , version 1 (04-12-2023)

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Alexis Joly, Christophe Botella, Lukáš Picek, Stefan Kahl, Hervé Goëau, et al.. Overview of LifeCLEF 2023: evaluation of AI models for the identification and prediction of birds, plants, snakes and fungi. CLEF 2023 - 14th International Conference of the CLEF Association, Sep 2023, Thessalokini, Greece. pp.416-439, ⟨10.1007/978-3-031-42448-9_27⟩. ⟨hal-04322219⟩
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