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ID 113248
著者
Fujisawa, Akira Aomori University
キーワード
ASCII art
deep neural networks
classification
image feature
character feature
資料タイプ
学術雑誌論文
抄録
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.
掲載誌名
Journal of Software
ISSN
1796217X
出版者
Academy Publisher
13
10
開始ページ
559
終了ページ
572
発行日
2018-10
権利情報
Open Access Journal
EDB ID
出版社版DOI
出版社版URL
フルテキストファイル
言語
eng
著者版フラグ
出版社版
部局
理工学系