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LifeCLEF 2021 Teaser: Biodiversity Identification and Prediction Challenges
Conference proceeding   Peer reviewed

LifeCLEF 2021 Teaser: Biodiversity Identification and Prediction Challenges

Alexis Joly, Herve Goeau, Elijah Cole, Stefan Kahl, Lukas Picek, Herve Glotin, Benjamin Deneu, Maximilien Servajean, Titouan Lorieul, Willem-Pier Vellinga, …
ADVANCES IN INFORMATION RETRIEVAL, ECIR 2021, PT II, Vol.12657, pp.601-607
Lecture Notes in Computer Science
01-01-2021

Abstract

Computer Science, Information Systems Computer Science, Theory & Methods Science & Technology Computer Science Technology
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 2021 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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UN Sustainable Development Goals (SDGs)

This output has contributed to the advancement of the following goals:

#15 Life on Land

Source: SDGs in the Output

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