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Overview of FungiCLEF 2022: Fungi Recognition as an Open Set Classification Problem

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F22%3A43966114" target="_blank" >RIV/49777513:23520/22:43966114 - isvavai.cz</a>

  • Alternative codes found

    RIV/68407700:21230/22:00362993

  • Result on the web

    <a href="https://ceur-ws.org/Vol-3180/paper-157.pdf" target="_blank" >https://ceur-ws.org/Vol-3180/paper-157.pdf</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Overview of FungiCLEF 2022: Fungi Recognition as an Open Set Classification Problem

  • Original language description

    The main goal of the new LifeCLEF challenge, FungiCLEF 2022: Fungi Recognition as an Open Set Classification Problem, was to provide an evaluation ground for end-to-end fungi species recognition in an open class set scenario. An AI-based fungi species recognition system deployed in the Atlas of Danish Fungi helps mycologists to collect valuable data and allows users to learn about fungi species identification. Advances in fungi recognition from images and metadata will allow continuous improvement of the system deployed in this citizen science project. The training set is based on the Danish Fungi 2020 dataset and contains 295,938 photographs of 1,604 species. For testing, we provided a collection of 59,420 expert-approved observations collected in 2021. The test set includes 1,165 species from the training set and 1,969 unknown species, leading to an open-set recognition problem. This paper provides (i) a description of the challenge task and datasets, (ii) a summary of the evaluation methodology, (iii) a review of the systems submitted by the participating teams, and (iv) a discussion of the challenge results. © 2022 Copyright for this paper by its authors.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20205 - Automation and control systems

Result continuities

  • Project

    <a href="/en/project/SS05010008" target="_blank" >SS05010008: Detection, identification and monitoring of animals by advanced computer vision methods.</a><br>

  • Continuities

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

Others

  • Publication year

    2022

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Proceedings of the Working Notes of CLEF 2022 - Conference and Labs of the Evaluation Forum

  • ISBN

  • ISSN

    1613-0073

  • e-ISSN

  • Number of pages

    12

  • Pages from-to

    1970-1981

  • Publisher name

    CEUR-WS

  • Place of publication

    Bologna

  • Event location

    Bologna, Italy

  • Event date

    Sep 5, 2022

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article