Abstract
Building 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, species identification and inventory is a difficult and costly task, requiring large-scale automated approaches. The LifeCLEF lab has been promoting and evaluating advances in this domain since 2011 through the organization of multi-year challenges. The 2024 edition presented in this article proposes five data-driven challenges as a continuation of this effort: (i) BirdCLEF: bird species recognition in audio soundscapes, (ii)FungiCLEF: fungi recognition beyond 0-1 cost, (iii) GeoLifeCLEF: remote sensing based prediction of species, (iv) PlantCLEF: Multi-species identification in vegetation plot images, and (v) SnakeCLEF: snake recognition in medically important scenarios.
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This work has received funding from the European Union’s Horizon research and innovation program under grant agreement No. 101060639 (MAMBO project).
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Joly, A. et al. (2024). LifeCLEF 2024 Teaser: Challenges on Species Distribution Prediction and Identification. In: Goharian, N., et al. Advances in Information Retrieval. ECIR 2024. Lecture Notes in Computer Science, vol 14613. Springer, Cham. https://doi.org/10.1007/978-3-031-56072-9_3
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