Original title: Right Convolutional Neural Network For Classification Illustrations In Artworks
Authors: Sikora, Pavel
Document type: Papers
Language: eng
Publisher: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
Abstract: This paper deals with the image classification problem in the field of artworks. The articleuses a custom dataset from artworks with eight classes of some not common objects and illustrations.This dataset is used to train three convolutional neural networks for classification. All classificationresults are well discussed and evaluated with an example on the images from a dataset.
Keywords: artwork; convolutional neural network; deep learning; image classification; keras; machinelearning
Host item entry: Proceedings I of the 27st Conference STUDENT EEICT 2021: General papers, ISBN 978-80-214-5942-7

Institution: Brno University of Technology (web)
Document availability information: Fulltext is available in the Brno University of Technology Digital Library.
Original record: http://hdl.handle.net/11012/200701

Permalink: http://www.nusl.cz/ntk/nusl-447746


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Universities and colleges > Public universities > Brno University of Technology
Conference materials > Papers