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.

Original languageEnglish
Title of host publicationProceedings - 2020 IEEE Winter Conference on Applications of Computer Vision, WACV 2020
Number of pages9
PublisherInstitute of Electrical and Electronics Engineers Inc.
Publication date2020
Pages2305-2313
Article number9093624
ISBN (Electronic)9781728165530
DOIs
Publication statusPublished - 2020
Event2020 IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2020 - Snowmass Village, United States
Duration: 1 Mar 20205 Mar 2020

Conference

Conference2020 IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2020
LandUnited States
BySnowmass Village
Periode01/03/202005/03/2020
SponsorCVF, IEEE Computer Society
SeriesProceedings - 2020 IEEE Winter Conference on Applications of Computer Vision, WACV 2020

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© 2020 IEEE.

ID: 270674410