Fungi recognition: A practical use case
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The paper presents a system for visual recognition of 1394 fungi species based on deep convolutional neural networks and its deployment in a citizen-science project. The system allows users to automatically identify observed specimens, while providing valuable data to biologists and computer vision researchers. The underlying classification method scored first in the FGVCx Fungi Classification Kaggle competition organized in connection with the Fine-Grained Visual Categorization (FGVC) workshop at CVPR 2018. We describe our winning submission and evaluate all technicalities that increased the recognition scores, and discuss the issues related to deployment of the system via the web- and mobile- interfaces.
Originalsprog | Engelsk |
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Titel | Proceedings - 2020 IEEE Winter Conference on Applications of Computer Vision, WACV 2020 |
Antal sider | 9 |
Forlag | Institute of Electrical and Electronics Engineers Inc. |
Publikationsdato | 2020 |
Sider | 2305-2313 |
Artikelnummer | 9093624 |
ISBN (Elektronisk) | 9781728165530 |
DOI | |
Status | Udgivet - 2020 |
Begivenhed | 2020 IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2020 - Snowmass Village, USA Varighed: 1 mar. 2020 → 5 mar. 2020 |
Konference
Konference | 2020 IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2020 |
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Land | USA |
By | Snowmass Village |
Periode | 01/03/2020 → 05/03/2020 |
Sponsor | CVF, IEEE Computer Society |
Navn | Proceedings - 2020 IEEE Winter Conference on Applications of Computer Vision, WACV 2020 |
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Bibliografisk note
Funding Information:
MS was supported by CTU student grant SGS17/185/OHK3/3T/13. LP was supported by the Ministry of Education, Youth and Sports of the Czech Republic project No. LO1506, and by the grant of the UWB project No. SGS-2019-027. JM was supported by OP VVV project CZ.02.1.01/0.0/0.0/16 019/0000765 Research Center for Informatics. The Danish Fungal Atlas was supported by Aage V. Jensen Naturfond.
Publisher Copyright:
© 2020 IEEE.
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