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
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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
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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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
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ISSN
1613-0073
e-ISSN
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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
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