Recognition of the Amazonian Flora by Inception Networks with Test-time Class Prior Estimation - CMP submission to PlantCLEF 2019
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00332912" target="_blank" >RIV/68407700:21230/19:00332912 - isvavai.cz</a>
Result on the web
<a href="http://ceur-ws.org/Vol-2380/" target="_blank" >http://ceur-ws.org/Vol-2380/</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Recognition of the Amazonian Flora by Inception Networks with Test-time Class Prior Estimation - CMP submission to PlantCLEF 2019
Original language description
The paper describes an automatic system for recognition of 10,000 plant species, with focus on species from the Guiana shield and the Amazon rain forest. The proposed system achieves the best results on the PlantCLEF 2019 test set with 31.9% accuracy. Compared against human experts in plant recognition, the system performed better than 3 of the 5 participating human experts and achieved 41.0% accuracy on the subset for expert evaluation. The proposed system is based on the Inception-v4 and Inception-ResNet-v2 Convolutional Neural Network (CNN) architectures. Performance improvements were achieved by: adjusting the CNN predictions according to the estimated change of the class prior probabilities, replacing network parameters with their running averages, testtime data augmentation, filtering the provided training set and adding additional training images from GBIF.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/EF16_019%2F0000765" target="_blank" >EF16_019/0000765: Research Center for Informatics</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Working Notes of CLEF 2019 - Conference and Labs of the Evaluation Forum
ISBN
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ISSN
1613-0073
e-ISSN
1613-0073
Number of pages
9
Pages from-to
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Publisher name
CEUR-WS.org
Place of publication
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Event location
Lugano
Event date
Sep 9, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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