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PDPモデルによる手書き漢字と平仮名の区別
https://ipsj.ixsq.nii.ac.jp/records/53445
https://ipsj.ixsq.nii.ac.jp/records/534457a8714df-a9f9-48cb-b537-54d0fc3aa323
名前 / ファイル | ライセンス | アクション |
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Copyright (c) 1992 by the Information Processing Society of Japan
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オープンアクセス |
Item type | SIG Technical Reports(1) | |||||||
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公開日 | 1992-01-23 | |||||||
タイトル | ||||||||
タイトル | PDPモデルによる手書き漢字と平仮名の区別 | |||||||
タイトル | ||||||||
言語 | en | |||||||
タイトル | Distinction between Hand - written Kanji and Hiragana Characters Using a PDP Model | |||||||
言語 | ||||||||
言語 | jpn | |||||||
資源タイプ | ||||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_18gh | |||||||
資源タイプ | technical report | |||||||
著者所属 | ||||||||
大阪電気通信大学工学部 | ||||||||
著者所属(英) | ||||||||
en | ||||||||
Faculty of Engineering, Osaka Electro - Communication University | ||||||||
著者名 |
梅田, 三千雄
× 梅田, 三千雄
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著者名(英) |
Michio, Umeda
× Michio, Umeda
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論文抄録 | ||||||||
内容記述タイプ | Other | |||||||
内容記述 | This paper discusses a new distinction system between hand-written Kanji and Hiragana characters using a PDP model. In this system two different types of features are extracted from character patterns. One is a Hough transformed feature which consists of 40 78 or 156 elements. Another is a local direction contributivity (LDC) feature which consists of 64 or 256 elements. A 3-layered artificial neural network based on a parallel distributed processing model is utilized for the distinction. The experimental result shows that the correct distinction rate is above 99% for learned characters data and is about 95% for unlearned characters but same category data. But the rate is less than 90% for unlerned Kanji category data. | |||||||
論文抄録(英) | ||||||||
内容記述タイプ | Other | |||||||
内容記述 | This paper discusses a new distinction system between hand-written Kanji and Hiragana characters using a PDP model. In this system, two different types of features are extracted from character patterns. One is a Hough transformed feature which consists of 40, 78 or 156 elements. Another is a local direction contributivity (LDC) feature which consists of 64 or 256 elements. A 3-layered artificial neural network based on a parallel distributed processing model is utilized for the distinction. The experimental result shows that the correct distinction rate is above 99% for learned characters data and is about 95% for unlearned characters but same category data. But, the rate is less than 90% for unlerned Kanji category data. | |||||||
書誌レコードID | ||||||||
収録物識別子タイプ | NCID | |||||||
収録物識別子 | AA11131797 | |||||||
書誌情報 |
情報処理学会研究報告コンピュータビジョンとイメージメディア(CVIM) 巻 1992, 号 7(1991-CVIM-076), p. 203-210, 発行日 1992-01-23 |
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Notice | ||||||||
SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc. | ||||||||
出版者 | ||||||||
言語 | ja | |||||||
出版者 | 情報処理学会 |