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LifeCLEF 2025 Teaser: Challenges on Species Presence Prediction and Identification, and Individual Animal Identification

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00384658" target="_blank" >RIV/68407700:21230/25:00384658 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1007/978-3-031-88720-8_57" target="_blank" >https://doi.org/10.1007/978-3-031-88720-8_57</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-031-88720-8_57" target="_blank" >10.1007/978-3-031-88720-8_57</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    LifeCLEF 2025 Teaser: Challenges on Species Presence Prediction and Identification, and Individual Animal Identification

  • Original language description

    Accurate identification, monitoring, and understanding of species distribution is important for biodiversity conservation, invasive species control, understanding climate change, and ecosystem management. Current methodologies for species identification, animal re-identification, and large-scale population monitoring are both resource-intensive and technically complex, posing significant challenges for widespread implementation. This highlights a need for automated, scalable solutions to enhance efficiency and accuracy. Since 2011, the LifeCLEF lab has driven progress in this field by organizing annual challenges to promote innovation in biodiversity informatics. The 2025 edition introduces five – one new, and four continued – data-driven tasks aimed at addressing current challenges in species recognition: (i) AnimalCLEF: multi-species individual animal identification, (ii) BirdCLEF: bird species identification in soundscape recordings, (iii) FungiCLEF: few shot classification with rare fungi species, (iv) GeoLifeCLEF: multi-modal species prediction using remote sensing and large-scale biodiversity data, and (v) PlantCLEF: multi-species plant identification in vegetation plot images.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/SS73020004" target="_blank" >SS73020004: FunDive: Monitoring and mapping fungal diversity for nature conservation</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2025

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Advances in Information Retrieval

  • ISBN

    978-3-031-88720-8

  • ISSN

    0302-9743

  • e-ISSN

    1611-3349

  • Number of pages

    9

  • Pages from-to

    373-381

  • Publisher name

    Springer International Publishing

  • Place of publication

    Cham

  • Event location

    Lucca

  • Event date

    Apr 6, 2025

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article