Overview of FungiCLEF 2023: Fungi Recognition Beyond 1/0 Cost
| dc.contributor.author | Picek, Lukáš | |
| dc.contributor.author | Šulc, Milan | |
| dc.contributor.author | Chamidullin, Rail | |
| dc.contributor.author | Matas, Jiří | |
| dc.date.accessioned | 2025-06-20T08:44:04Z | |
| dc.date.available | 2025-06-20T08:44:04Z | |
| dc.date.issued | 2023 | |
| dc.date.updated | 2025-06-20T08:44:04Z | |
| dc.description.abstract | 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. | en |
| dc.format | 11 | |
| dc.identifier.isbn | neuvedeno | |
| dc.identifier.issn | 1613-0073 | |
| dc.identifier.obd | 43940700 | |
| dc.identifier.orcid | Picek, Lukáš 0000-0002-6041-9722 | |
| dc.identifier.orcid | Chamidullin, Rail 0000-0003-1728-8939 | |
| dc.identifier.uri | http://hdl.handle.net/11025/60819 | |
| dc.language.iso | en | |
| dc.project.ID | SGS-2022-017 | |
| dc.project.ID | SS05010008 | |
| dc.publisher | CEUR-WS | |
| dc.relation.ispartofseries | 24th Working Notes of the Conference and Labs of the Evaluation Forum, CLEF-WN 2023 | |
| dc.subject | classification | en |
| dc.subject | computer vision | en |
| dc.subject | fine grained visual categorization | en |
| dc.subject | fungi | en |
| dc.subject | FungiCLEF | en |
| dc.subject | LifeCLEF | en |
| dc.subject | machine learning | en |
| dc.subject | metadata | en |
| dc.subject | open-set recognition | en |
| dc.subject | species identification | en |
| dc.title | Overview of FungiCLEF 2023: Fungi Recognition Beyond 1/0 Cost | en |
| dc.type | Stať ve sborníku (D) | |
| dc.type | STAŤ VE SBORNÍKU | |
| dc.type.status | Published Version | |
| local.files.count | 1 | * |
| local.files.size | 7354136 | * |
| local.has.files | yes | * |
| local.identifier.eid | 2-s2.0-85175659725 |
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