Overview of FungiCLEF 2023: Fungi Recognition Beyond 1/0 Cost

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F23%3A43969699" target="_blank" >RIV/49777513:23520/23:43969699 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21230/23:00371790
Result on the web
<a href="https://ceur-ws.org/Vol-3497/paper-165.pdf" target="_blank" >https://ceur-ws.org/Vol-3497/paper-165.pdf</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Overview of FungiCLEF 2023: Fungi Recognition Beyond 1/0 Cost
Original language description
Computer vision systems for fungi recognition aid mycologists, researchers, and enthusiasts in the efficient identification of mushroom species. FungiCLEF 2023, the second edition of the fungi recognition challenge at LifeCLEF, builds upon the Danish Fungi 2020 dataset and upon its predecessor by presenting several recognition tasks differing in the cost functions corresponding to different practical scenarios, including poisonous/edible decision-making or discovering unseen species. With practical applications in mind, the 2023 challenge only accepted submissions with model size under 1GB. The competition received 16 final submissions from 3 teams. This overview paper provides a detailed description of the challenge data and tasks, a review of the submitted methods, and a discussion of the results.
Czech name
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Czech description
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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)

Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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