Kazan (Volga region) Federal University, KFU
KAZAN
FEDERAL UNIVERSITY
 
HIERARCHICAL CONVOLUTIONAL NEURAL NETWORK FOR HANDWRITTEN DIGITS RECOGNITION
Form of presentationArticles in international journals and collections
Year of publication2020
Языканглийский
  • Kayumov Zufar Damirovich, author
  • Mosin Sergey Gennadevich, author
  • Tumakov Dmitriy Nikolaevich, author
  • Kayumov Zufar Damirovich, author
  • Bibliographic description in the original language Kayumov Z, Tumakov D, Mosin S., Hierarchical Convolutional Neural Network for Handwritten Digits Recognition//Procedia Computer Science. - 2020. - Vol.171, Is.. - P.1927-1934.
    Annotation The application of a combination of convolutional neural networks for the recognition of handwritten digits is considered. Recognition is carried out by two sets of the networks following each other. The first neural network selects two digits with maximum activation functions. Depending on the winners, the next network is activated, which selects one digit from two. The proposed algorithm is tested on the data from MNIST. The minimal handwriting recognition error was estimated with this approach.
    Keywords Handwritten digits; recognition; Hierarchical convolutional neural network; MNIST
    The name of the journal Procedia Computer Science
    URL https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086633513&doi=10.1016%2fj.procs.2020.04.206&partnerID=40&md5=9253c2b4e454acd44d8a54426cf8bf70
    Please use this ID to quote from or refer to the card https://repository.kpfu.ru/eng/?p_id=235382&p_lang=2

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