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LifeCLEF 2020 Teaser: Biodiversity Identification and Prediction Challenges

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, the difficulty of identifying plants and animals in the field is hindering the aggregation of new data and knowledge. Identifying and naming living plants or animals 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 2020 edition proposes four data-oriented challenges related to the identification and prediction of biodiversity: (i) PlantCLEF: cross-domain plant identification based on herbarium sheets, (ii) BirdCLEF: bird species recognition in audio soundscapes, (iii) GeoLifeCLEF: location-based prediction of species based on environmental and occurrence data, and (iv) SnakeCLEF: image-based snake identification.
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https://hal.inrae.fr/hal-02873670
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Submitted on : Monday, July 13, 2020 - 10:37:26 AM
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Alexis Joly, Hervé Goëau, Christophe Botella, Rafael Ruiz de Castaneda, Hervé Glotin, et al.. LifeCLEF 2020 Teaser: Biodiversity Identification and Prediction Challenges. 42nd European Conference on IR Research on Advances in Information Retrieval (ECIR), Apr 2020, Lisbon, Portugal. pp.542-549, ⟨10.1007/978-3-030-45442-5_70⟩. ⟨hal-02873670⟩

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