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Recurrent-neural-network-based error correction of tapping touchscreen in nonstationary vibrating environment
https://doi.org/10.14988/00027855
https://doi.org/10.14988/00027855d139d404-90ef-49b3-b5aa-ff9cf2cbac16
名前 / ファイル | ライセンス | アクション |
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023061040004.pdf (601.4 kB)
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Item type | 紀要論文 / Departmental Bulletin Paper(1) | |||||
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公開日 | 2021-02-03 | |||||
タイトル | ||||||
言語 | en | |||||
タイトル | Recurrent-neural-network-based error correction of tapping touchscreen in nonstationary vibrating environment | |||||
言語 | ||||||
言語 | eng | |||||
キーワード | ||||||
主題 | ずれ補正, タッチスクリーン, スマートフォン, タッピング, 再帰型ニューラルネットワーク error correction, touchscreen, smartphone, tapping, Recurrent Neaural Network (RNN) |
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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 | departmental bulletin paper | |||||
ID登録 | ||||||
ID登録 | 10.14988/00027855 | |||||
ID登録タイプ | JaLC | |||||
アクセス権 | ||||||
アクセス権 | open access | |||||
アクセス権URI | http://purl.org/coar/access_right/c_abf2 | |||||
その他(別言語等)のタイトル | ||||||
その他のタイトル | 再帰型ニューラルネットワークを用いた非定常振動環境におけるタッチスクリーンタップ位置補正 | |||||
言語 | ja | |||||
その他(別言語等)のタイトル | ||||||
その他のタイトル | サイキガタ ニューラル ネットワーク オ モチイタ ヒテイジョウ シンドウ カンキョウ ニオケル タッチ スクリーン タップ イチ ホセイ | |||||
言語 | ja-Kana | |||||
著者 |
鈴木, 優
× 鈴木, 優× 加藤, 恒夫 |
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著者所属 | ||||||
ja | ||||||
加藤, 恒夫 / 同志社大学理工学部インテリジェント情報工学科准教授 | ||||||
著者所属(英) | ||||||
en | ||||||
Suzuki, Yu / Graduate School of Science and Engineering, Doshisha University | ||||||
著者所属(英) | ||||||
en | ||||||
Kato, Tsuneo / Faculty of Science and Engineering, Doshisha University | ||||||
所属機関識別子種別 | ||||||
値 | kakenhi | |||||
所属機関識別子 | ||||||
値 | 34310 | |||||
抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | 振動環境でタッチスクリーン入力を行うと,意図したキーと異なる入力が増えてしまう.このタップ位置のずれはタップ直前の振動と関係していると考えられる.本研究では走行中のバス車内でスマートフォン文字入力のタッピングデータを収集し,内蔵加速度センサから得られる加速度信号をもとに再帰型ニューラルネットワークを用いてタップ位置ずれを推定・補正する方法を検討した.その結果,14名分のユーザ依存モデルにより,タップ位置ずれの二乗平均平方根誤差がx軸,y軸方向でそれぞれ平均3.1%,8.4%削減されることを確認した. | |||||
言語 | ja | |||||
抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | Tapping a touchscreen in a vibrating environment causes more errors than in a non-vibrating environment. We collected tapping data from participants using smartphones with triaxial acceleration signals while riding a local bus, typical nonstationary vibrating environments, and developed a recurrent-neural network-based positional-error correction model with an input of acceleration signals. The experimental results indicated that the proposed model reduced the root mean square error by 3.1% on the x-axis and 8.4% on the y-axis on average. However, the reduction rates were highly user-dependent. | |||||
言語 | en | |||||
書誌情報 |
ja : 同志社大学ハリス理化学研究報告 en : The Harris science review of Doshisha University 巻 61, 号 4, p. 209-214, 発行日 2021-01-31 |
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出版者 | ||||||
言語 | ja | |||||
出版者 | 同志社大学ハリス理化学研究所 | |||||
出版者(英) | ||||||
言語 | en | |||||
出版者 | Harris Science Research Institute of Doshisha University | |||||
ISSN | ||||||
収録物識別子タイプ | PISSN | |||||
収録物識別子 | 21895937 | |||||
書誌レコードID | ||||||
収録物識別子タイプ | NCID | |||||
収録物識別子 | AA12716107 | |||||
権利者情報 | ||||||
権利者名 | 同志社大学ハリス理化学研究所 | |||||
言語 | ja | |||||
権利者名 | Harris Science Research Institute of Doshisha University | |||||
言語 | en | |||||
関連サイト | ||||||
関連タイプ | isFormatOf | |||||
識別子タイプ | URI | |||||
関連識別子 | https://doors.doshisha.ac.jp/opac/opac_link/bibid/SB12902196/?lang=0 | |||||
言語 | ja | |||||
関連名称 | 掲載刊行物所蔵情報へのリンク / Link to Contents | |||||
フォーマット | ||||||
内容記述タイプ | Other | |||||
内容記述 | application/pdf | |||||
出版タイプ | ||||||
出版タイプ | VoR | |||||
出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
日本十進分類法 | ||||||
主題 | 694.6 |