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ID 113248
Author
Fujisawa, Akira Aomori University
Keywords
ASCII art
deep neural networks
classification
image feature
character feature
Content Type
Journal Article
Description
In recent years, a lot of non-verbal expressions have been used on social media. Ascii art (AA) is an expression using characters with visual technique. In this paper, we set up an experiment to classify AA pictures by using character features and image features. We try to clarify which feature is more effective for a method to classify AA pictures. We proposed four methods: 1) a method based on character frequency, 2) a method based on character importance value and 3) a method based on image features, 4) a method based on image features using pre-trained neural networks and 5) a method based on image features of characters. We trained neural networks by using these five features. In the experimental result, the best classification accuracy was obtained in the feed forward neural networks that used image features of characters.
Journal Title
Journal of Software
ISSN
1796217X
Publisher
Academy Publisher
Volume
13
Issue
10
Start Page
559
End Page
572
Published Date
2018-10
Rights
Open Access Journal
EDB ID
DOI (Published Version)
URL ( Publisher's Version )
FullText File
language
eng
TextVersion
Publisher
departments
Science and Technology