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Computer Optics, 2020, Volume 44, Issue 2, Pages 236–243
DOI: https://doi.org/10.18287/2412-6179-CO-601
(Mi co785)
 

This article is cited in 7 scientific papers (total in 7 papers)

IMAGE PROCESSING, PATTERN RECOGNITION

Classification of rare traffic signs

B. V. Faizova, V. I. Shakhuroa, V. V. Sanzharovba, A. S. Konouchineca

a Lomonosov Moscow State University, Moscow, Russia
b Gubkin RSU of Oil and Gas
c NRU Higher School of Economics, Moscow, Russia
References:
Abstract: The paper studies the possibility of using neural networks for the classification of objects that are few or absent at all in the training set. The task is illustrated by the example of classification of rare traffic signs. We consider neural networks trained using a contrastive loss function and its modifications, also we use different methods for generating synthetic samples for classification problems. As a basic method, the indexing of classes using neural network features is used. A comparison is made of classifiers trained with three different types of synthetic samples and their mixtures with real data. We propose a method of classification of rare traffic signs using a neural network discriminator of rare and frequent signs. The experimental evaluation shows that the proposed method allows rare traffic signs to be classified without significant loss of frequent sign classification quality.
Keywords: traffic sign classification, synthetic training samples, neural networks, image recognition, image transforms, neural network compositions.
Funding agency Grant number
Russian Foundation for Basic Research 18-31-20032 мол_а_вед
17-71-20072 мол_а
This work was supported by the Russian Science Foundation under RSF grant 18-31-20032 ("Physically correct lighting modeling and image synthesis on massively parallel computing systems in applications of artificial intelligence") and the Russian Science Foundation under RSF grant 17-71-20072 ("Deep Bayesian Methods in Machine Learning, Scalable Optimization and Computer Vision Problems").
Received: 22.07.2019
Accepted: 11.10.2019
Document Type: Article
Language: Russian
Citation: B. V. Faizov, V. I. Shakhuro, V. V. Sanzharov, A. S. Konouchine, “Classification of rare traffic signs”, Computer Optics, 44:2 (2020), 236–243
Citation in format AMSBIB
\Bibitem{FaiShaSan20}
\by B.~V.~Faizov, V.~I.~Shakhuro, V.~V.~Sanzharov, A.~S.~Konouchine
\paper Classification of rare traffic signs
\jour Computer Optics
\yr 2020
\vol 44
\issue 2
\pages 236--243
\mathnet{http://mi.mathnet.ru/co785}
\crossref{https://doi.org/10.18287/2412-6179-CO-601}
Linking options:
  • https://www.mathnet.ru/eng/co785
  • https://www.mathnet.ru/eng/co/v44/i2/p236
  • This publication is cited in the following 7 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Computer Optics
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