Text detection algorithm on real scenes images and videos on the base of discrete cosine transform and convolutional neural network; Control and Communications (SIBCON-2017)

Text detection algorithm on real scenes images and videos on the base of discrete cosine transform and convolutional neural network; Control and Communications (SIBCON-2017)

Bibliografische gegevens
Parent link:	Control and Communications (SIBCON-2017).— 2017.— [17082656]
Coauteur:	Томский политехнический университет Институт кибернетики, ИК
Andere auteurs:	Osina P. M. Polina Maksimovna, Bolotova Yu. A. Yuliya Aleksandrovna, Spitsyn V. G. Vladimir Grigorievich
Samenvatting:	Title screen In this work we present algorithms which are applied in such task as text recognition on images and video. Proposed algorithm is based on the combination of discrete cosine transform and convolutional neural networks. Description of the applying features of discrete cosine transform for text detection is provided. We list the main advantages and disadvantages of CNN and DCT combination. Also in this article we are going to consider methods of convolution neural networks for the task of text recognition. Режим доступа: по договору с организацией-держателем ресурса
Taal:	Engels
Gepubliceerd in:	2017
Onderwerpen:	электронный ресурс труды учёных ТПУ text detection discrete cosine transform artificial neural network convolution neural networks machine learning optical character recognition тексты преобразование нейронные сети машинное обучение оптическое распознавание символы
Online toegang:	https://doi.org/10.1109/SIBCON.2017.7998591
Formaat:	Elektronisch Hoofdstuk
KOHA link:	https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=656804

Internet

https://doi.org/10.1109/SIBCON.2017.7998591