Fungi Recognition: A Practical Use Case

Fungi Recognition: A Practical Use Case

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...

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Bibliographic Details
Published in:2020 IEEE Winter Conference on Applications of Computer Vision (WACV) pp. 2305 - 2313
Main Authors: Sulc, Milan, Picek, Lukas, Matas, Jiri, Jeppesen, Thomas S., Heilmann-Clausen, Jacob
Format: Conference Proceeding
Language:English
Published: IEEE 01-03-2020
Subjects:
Agriculture
Biodiversity
Computer vision
Fungi
Image recognition
Training
Visualization
Online Access:Get full text
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Summary: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.
ISSN:2642-9381
DOI:10.1109/WACV45572.2020.9093624