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ŠŮSTEK, M. VÍDEŇSKÝ, F. ZBOŘIL, F. ZBOŘIL, F.
Originální název
Family Coat of Arms and Armorial Achievement Classification
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
This paper presents an approach to classification of family coats of arms and armorial achievement. It is difficult to obtain images with coats of arms because not many of them are publicly available. To the best of our knowledge, there is no dataset. Therefore, we artificially extend our dataset using Neural Style Transfer technique and simple image transformations. We describe our dataset and the division into training and test sets that respects the lack of data examples. We discuss results obtained with both small convolutional neural network (convnet) trained from scratch and modified architectures of various convents pretrained on Imagenet dataset. This paper further focuses on the VGG architecture which produces the best accuracy. We show accuracy progress during training, per-class accuracy and a normalized confusion matrix for VGG16 architecture. We reach top-1 accuracy of nearly 60% and top-5 accuracy of 80%. To the best of our knowledge, this is the first family coats of arms classification work, so we cannot compare our results with others.
Klíčová slova
coats of arms, image classification, convolutional neural network, artificial intelligence, machine learning
Autoři
ŠŮSTEK, M.; VÍDEŇSKÝ, F.; ZBOŘIL, F.; ZBOŘIL, F.
Vydáno
17. 4. 2019
Nakladatel
Springer International Publishing
Místo
Los Alamitos
ISSN
2194-5357
Periodikum
Advances in Intelligent Systems and Computing
Ročník
941
Číslo
2
Stát
Švýcarská konfederace
Strany od
577
Strany do
586
Strany počet
9
URL
https://www.fit.vut.cz/research/publication/11848/
BibTex
@inproceedings{BUT156844, author="Martin {Šůstek} and František {Vídeňský} and František {Zbořil} and František {Zbořil}", title="Family Coat of Arms and Armorial Achievement Classification", booktitle="Intelligent Systems Design and Applications", year="2019", series="Advances in Intelligent Systems and Computing", journal="Advances in Intelligent Systems and Computing", volume="941", number="2", pages="577--586", publisher="Springer International Publishing", address="Los Alamitos", doi="10.1007/978-3-030-16660-1\{_}56", issn="2194-5357", url="https://www.fit.vut.cz/research/publication/11848/" }