Rchr
J-GLOBAL ID：200901041714259888   Update date: Aug. 05, 2024

Yoshifumi Okada

オカダ ヨシフミ | Yoshifumi Okada
Affiliation and department：
Muroran Institute of Technology College of Information and Systems System Informatics Research Unit

About Muroran Institute of Technology College of Information and Systems System Informatics Research Unit


Job title： Professor
Other affiliations (1)：
  • Muroran Institute of Technology  Department of Sciences and Informatics Course of Mathematical Science and Informatics   Professor
Research field  (2)： Other ,  Other
Research keywords  (7)： Deep learning and its applications ,  Data mining and its applications ,  Biometrics ,  Emotion recognition ,  Gene expression data analysis ,  ECG analysis ,  Kansei-based information retrieval
Research theme for competitive and other funds  (6)：
  • 2023 - 2026 心電図を用いて多種類の心疾患の識別を実現する軽量な深層学習モデルの開発
  • 2020 - 2022 心電図から疑わしい心疾患への絞り込みを可能にする自動識別システムの開発
  • 2017 - 2019 連鎖パタンマイニングを用いた心電図異常検出
  • 2012 - 2013 多クラスの大規模感性データを対象とした概念マイニングシステムの開発
  • 2010 - 2011 乳児泣き声の音響特性に基づく「舌癒着症」の自動診断法の開発
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Papers (85)：
  • Momoko Ishimaru, Yoshifumi Okada, Ryunosuke Uchiyama, Ryo Horiguchi, Itsuki Toyoshima. A New Regression Model for Depression Severity Prediction Based on Correlation among Audio Features Using a Graph Convolutional Neural Network. Diagnostics. 2023. 13. 4
  • Itsuki Toyoshima, Yoshifumi Okada, Momoko Ishimaru, Ryunosuke Uchiyama, Mayu Tada. Multi-Input Speech Emotion Recognition Model Using Mel Spectrogram and GeMAPS. Sensors. 2023. 23. 3
  • Vivat Thongchotcha, Yasuo Kudo, Yoshifumi Okada, Kazuhiko Sato. Educational Recommendation System Utilizing Learning Styles: A Systematic Literature Review. IEEE Access. 2023. 11. 8988-8999
  • Momoko Ishimaru, Yoshifumi Okada, Ryunosuke Uchiyama, Ryo Horiguchi, Itsuki Toyoshima. Classification of Depression and Its Severity Based on Multiple Audio Features Using a Graphical Convolutional Neural Network. International Journal of Environmental Research and Public Health. 2023. 20. 2
  • Ryunosuke Uchiyama, Yoshifumi Okada, Ryuya Kakizaki, Sekito Tomioka. End-to-End Convolutional Neural Network Model to Detect and Localize Myocardial Infarction Using 12-Lead ECG Images without Preprocessing. Bioengineering-Basel. 2022. 9. 9
ｍore...
Books (6)：
  • 現代社会と情報システム
    朝倉書店 2020 ISBN:9784254122534
  • Biometrics and Kansei Engineering
    Springer 2012
  • Intelligent Control and Innovative Computing
    Springer 2012
  • マイクロアレイ データ統計解析プロトコール
    羊土社 2008
  • バイオデータベースとウェブツールの手とり足とり活用法
    羊土社 2007
ｍore...
Awards (10)：
  • 2018/11 - 日本感性工学会 生命ソフトウェア部会 生命ソフトウェア・感性工房・而立の会合同シンポジウム2018 優秀発表賞
  • 2017/05 - International Association of Engineers Certificate of Merit for The 2017 IAENG International Conference on Computer Science
  • 2016/05 - International Association of Engineers Best Paper Award of The IAENG International Conference on Artificial Intelligence and Applications
  • 2012/08 - コンピュータ利用協議会 CIEC学会賞(論文賞)
  • 2012/08 - 日本工学教育協会 日本工学教育協会賞(業績賞)
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