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Detecting Erase Strokes from Online Handwritten Notes using Support Vector Classification
http://hdl.handle.net/10228/5582
http://hdl.handle.net/10228/5582034bebe6-d20f-412c-a349-df0ef7dc5750
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
PCS60_952.pdf (1.0 MB)
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| アイテムタイプ | 学術雑誌論文 = Journal Article(1) | |||||
|---|---|---|---|---|---|---|
| 公開日 | 2016-03-03 | |||||
| 資源タイプ | ||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
| 資源タイプ | journal article | |||||
| タイトル | ||||||
| タイトル | Detecting Erase Strokes from Online Handwritten Notes using Support Vector Classification | |||||
| 言語 | en | |||||
| 言語 | ||||||
| 言語 | eng | |||||
| 著者 |
Miura, Motoki
× Miura, Motoki× Kobayashi, Yusaku |
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| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | We have implemented a student note-sharing system, AirTransNote, that facilitates collaborative and interactive learning in conven- tional classrooms. With the AirTransNote system, a teacher can immediately share student notes with the class using a projection screen to enhance group learning. However, students tend to hesitate to share their notes, particularly when the notes contain embarrassing mistakes. Nevertheless, teachers want to focus on real mistakes students make while learning. We introduce an erase stroke detecting method for the student note-sharing system to reduce students’ discomfort regarding sharing mistakes, as well as to assist the teacher in finding mistakes. We collected and manually labeled free-style handwritten student notes. Based on the labeled notes, we extracted features for the erase symbols and deleted strokes. We have tested support vector machine techniques for classifying erase symbols and deleted strokes from typical handwritten notes. | |||||
| 言語 | en | |||||
| 備考 | ||||||
| 内容記述タイプ | Other | |||||
| 内容記述 | Knowledge-Based and Intelligent Information & Engineering Systems 19th Annual Conference, KES-2015, Singapore, September 2015 Proceedings | |||||
| 書誌情報 |
en : Procedia Computer Science 巻 60, p. 952-959, 発行日 2015-09-01 |
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| 出版社 | ||||||
| 出版者 | Elsevier | |||||
| DOI | ||||||
| 関連タイプ | isIdenticalTo | |||||
| 識別子タイプ | DOI | |||||
| 関連識別子 | https://doi.org/10.1016/j.procs.2015.08.131 | |||||
| ISSN | ||||||
| 収録物識別子タイプ | EISSN | |||||
| 収録物識別子 | 1877-0509 | |||||
| 著作権関連情報 | ||||||
| 権利情報Resource | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |||||
| 権利情報 | Copyright (c) 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | Handwriting Recognition | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | Learning Attitudes | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | Anoto digital pen | |||||
| 出版タイプ | ||||||
| 出版タイプ | VoR | |||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
| 査読の有無 | ||||||
| 値 | yes | |||||
| 研究者情報 | ||||||
| URL | https://hyokadb02.jimu.kyutech.ac.jp/html/138_ja.html | |||||
| 連携ID | ||||||
| 値 | 5356 | |||||
