Detail publikace

Right convolutional neural network for classification illustrations in artworks

SIKORA, P.

Originální název

Right convolutional neural network for classification illustrations in artworks

Typ

článek ve sborníku mimo WoS a Scopus

Jazyk

angličtina

Originální abstrakt

This paper deals with the image classification problem in the field of artworks. The article uses 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 classification results are well discussed and evaluated with an example on the images from a dataset.

Klíčová slova

artwork, convolutional neural network, deep learning, image classification, keras, machine learning

Autoři

SIKORA, P.

Vydáno

27. 4. 2021

Nakladatel

Brno University of Technology, Faculty of Electrical Engineering and Comunnication

Místo

Brno

ISBN

978-80-214-5942-7

Kniha

Proceedings of the 27th Conference STUDENT EEICT 2021

Edice

1

Strany od

591

Strany do

595

Strany počet

5

URL

https://www.fekt.vut.cz/conf/EEICT/archiv/sborniky/EEICT_2021_sbornik_1.pdf

BibTex

@inproceedings{BUT172262,
  author="Pavel {Sikora}",
  title="Right convolutional neural network for classification illustrations in artworks",
  booktitle="Proceedings of the 27th Conference STUDENT EEICT 2021",
  year="2021",
  series="1",
  pages="591--595",
  publisher="Brno University of Technology, Faculty of Electrical Engineering and Comunnication",
  address="Brno",
  isbn="978-80-214-5942-7",
  url="https://www.fekt.vut.cz/conf/EEICT/archiv/sborniky/EEICT_2021_sbornik_1.pdf"
}