Fungi Recognition: A Practical Use Case
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F20%3A43959882" target="_blank" >RIV/49777513:23520/20:43959882 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21230/20:00345767
Result on the web
<a href="https://ieeexplore.ieee.org/document/9093624" target="_blank" >https://ieeexplore.ieee.org/document/9093624</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/WACV45572.2020.9093624" target="_blank" >10.1109/WACV45572.2020.9093624</a>
Alternative languages
Result language
angličtina
Original language name
Fungi Recognition: A Practical Use Case
Original language description
The paper presents a system for visual recognition of1394 fungi species based on deep convolutional neuralnetworks and its deployment in a citizen-science project.The system allows users to automatically identify observedspecimens, while providing valuable data to biologists andcomputer vision researchers. The underlying classifica-tion method scored first in the FGVCx Fungi ClassificationKaggle competition organized in connection with the Fine-Grained Visual Categorization (FGVC) workshop at CVPR2018. We describe our winning submission and evaluate alltechnicalities that increased the recognition scores, and dis-cuss the issues related to deployment of the system via theweb- and mobile- interfaces.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
20205 - Automation and control systems
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2020 IEEE Winter Conference on Applications of Computer Vision (WACV)
ISBN
978-1-72816-553-0
ISSN
2472-6737
e-ISSN
2642-9381
Number of pages
9
Pages from-to
2305-2313
Publisher name
IEEE
Place of publication
Red Hook, NY
Event location
Snowmass Village, Colorado, USA
Event date
Mar 1, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000578444802040