Book chapter
English

LifeCLEF 2022 Teaser: An Evaluation of Machine-Learning Based Species Identification and Species Distribution Prediction

Published inHagen Matthias, et al. (Ed.), ECIR 2022: Advances in Information Retrieval, p. 390-399
PublisherCham : Springer
Collection
  • Lecture Notes in Computer Science; 13186
First online date2022-04-05
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, animals and fungi is hindering the aggregation of new data and knowledge. Identifying and naming living organisms 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 2022 edition proposes five data-oriented challenges related to the identification and prediction of biodiversity: (i) PlantCLEF: very large-scale plant identification, (ii) BirdCLEF: bird species recognition in audio soundscapes, (iii) GeoLifeCLEF: remote sensing based prediction of species, (iv) SnakeCLEF: Snake Species Identification in Medically Important scenarios, and (v) FungiCLEF: Fungi recognition from images and metadata.

Funding
  • European Commission - Co-designed Citizen Observatories Services for the EOS-Cloud [863463]
Citation (ISO format)
JOLY, Alexis et al. LifeCLEF 2022 Teaser: An Evaluation of Machine-Learning Based Species Identification and Species Distribution Prediction. In: ECIR 2022: Advances in Information Retrieval. Hagen Matthias, et al. (Ed.). Cham : Springer, 2022. p. 390–399. (Lecture Notes in Computer Science) doi: 10.1007/978-3-030-99739-7_49
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Book chapter (Published version)
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Identifiers
ISBN978-3-030-99738-0
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Creation01/04/2023 2:46:00 PM
First validation06/05/2023 11:14:54 AM
Update time06/05/2023 11:14:54 AM
Status update06/05/2023 11:14:54 AM
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