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Proceedings chapter
Open access
English

Overview of LifeCLEF 2021: An Evaluation of Machine-Learning Based Species Identification and Species Distribution Prediction

Presented at Virtual Event, September 21-24
PublisherCham : Springer
Collection
  • Lecture Notes in Computer Science; 12880
Publication date2021
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 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: remote sensing based prediction of species, and (iv) SnakeCLEF: Automatic Snake Species Identification with Country-Level Focus.

Funding
  • European Commission - Co-designed Citizen Observatories Services for the EOS-Cloud [863463]
Citation (ISO format)
JOLY, Alexis et al. Overview of LifeCLEF 2021: An Evaluation of Machine-Learning Based Species Identification and Species Distribution Prediction. In: Experimental IR Meets Multilinguality, Multimodality, and Interaction. CLEF 2021. Virtual Event. Cham : Springer, 2021. p. 371–393. (Lecture Notes in Computer Science) doi: 10.1007/978-3-030-85251-1_24
Main files (1)
Proceedings chapter (Accepted version)
accessLevelPublic
Identifiers
ISBN978-3-030-85250-4
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Technical informations

Creation09/14/2021 6:16:00 PM
First validation09/14/2021 6:16:00 PM
Update time03/16/2023 1:23:02 AM
Status update03/16/2023 1:23:00 AM
Last indexation05/06/2024 8:07:49 AM
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