ABURADA Kentaro

写真a

Affiliation

Engineering educational research section Information and Communication Technology Program

Title

Associate Professor

External Link

 

Papers 【 display / non-display

  • Proposal of ASLA Which Is a Segmentation and Labeling Tool for Document Images Based on Deep Learning Reviewed

    Kanta Kakinoki, Tetsuro Katayama, Yoshihiro Kita, Hisaaki Yamaba, Kentaro Aburada, Naonobu Okazaki

    The 2024 International Conference on Artificial Life and Robotics (ICAROB2024)   262 - 266   2024.2

     More details

    Language:Japanese   Publishing type:Research paper (international conference proceedings)   Publisher:Proceedings of International Conference on Artificial Life and Robotics  

    Writing VDM++ specifications is difficult. The existing method can automatically generate type and constant definitions in VDM++ specification from natural language specification using machine learning. This paper proposes a method to generate classes and instance variable definitions in the VDM++ specification from natural language specification to improve the usefulness of the existing method. From the evaluation experiment by using F-values, it has been confirmed that the proposed method can improve the usefulness of the existing method.

  • Extension to Support Types and Operation/Function Definitions in BWDM to Generate Test Case Tool from the VDM++ Specification Reviewed

    Shota Takakura, Tetsuro Katayama, Yoshihiro Kita, Hisaaki Yamaba, Kentaro Aburada, Naonobu Okazaki

    The 2024 International Conference on Artificial Life and Robotics (ICAROB2024)   257 - 261   2024.2

     More details

    Language:Japanese   Publishing type:Research paper (international conference proceedings)   Publisher:Proceedings of International Conference on Artificial Life and Robotics  

    Writing VDM++ specifications is difficult. The existing method can automatically generate type and constant definitions in VDM++ specification from natural language specification using machine learning. This paper proposes a method to generate classes and instance variable definitions in the VDM++ specification from natural language specification to improve the usefulness of the existing method. From the evaluation experiment by using F-values, it has been confirmed that the proposed method can improve the usefulness of the existing method.

  • Prototype of RAGESS Which Is a Tool for Automatically Generating SwiftDiagram to Support iOS App Development Reviewed

    Haruki Onaga, Tetsuro Katayama, Yoshihiro Kita, Hisaaki Yamaba, Kentaro Aburada, Naonobu Okazaki

    The 2024 International Conference on Artificial Life and Robotics (ICAROB2024)   252 - 256   2024.2

     More details

    Language:Japanese   Publishing type:Research paper (international conference proceedings)   Publisher:Proceedings of International Conference on Artificial Life and Robotics  

    Writing VDM++ specifications is difficult. The existing method can automatically generate type and constant definitions in VDM++ specification from natural language specification using machine learning. This paper proposes a method to generate classes and instance variable definitions in the VDM++ specification from natural language specification to improve the usefulness of the existing method. From the evaluation experiment by using F-values, it has been confirmed that the proposed method can improve the usefulness of the existing method.

  • On an improvement of hand gesture recognition for realizing an s-EMG based user authentication using finger spelling Reviewed

    Hisaaki Yamaba, Naoki Sawagashira, Kentaro Aburada, Tetsuro Katayama, Naonobu Okazaki

    Proc. 29th Int'l Sympo. on Artificial Life and Robotics 2024 (AROB 29th 2024)   933 - 938   2024.1

     More details

    Language:English   Publishing type:Research paper (international conference proceedings)  

  • Investigation of malware classification based on image representation Reviewed

    Hyoga Kawagoe, Shotaro Usuzaki, Kentaro Aburada, Hisaaki Yamaba, Tetsuro Katayama, Mirang Park, Naonobu Okazaki

    Proc. 29th Int'l Sympo. on Artificial Life and Robotics 2024 (AROB 29th 2024)   929 - 932   2024.1

     More details

    Authorship:Corresponding author   Language:English   Publishing type:Research paper (international conference proceedings)  

display all >>

Books 【 display / non-display

  • コンピュータネットワーク概論

    水野 忠則 , 中村 嘉隆, 田 学軍, 清原 良三, 石原 進, 久保田 真一郎, 岡崎 直宣, 太田 賢 (通信工学), 稲村 浩, 舟阪 淳一, 油田 健太郎( Role: Sole author)

    共立出版  2024  ( ISBN:9784320125766

     More details

    Language:Japanese Book type:Scholarly book

    CiNii Books

Awards 【 display / non-display

  • 火の国情報シンポジウム2022奨励賞

    2022.3   情報処理学会九州支部  

    永井 麻裕,他

     More details

    Award type:Award from Japanese society, conference, symposium, etc.  Country:Japan

  • Best Paper Award

    2019.11   BWCCA-2019  

    渡辺 一樹,他

     More details

    Award type:Award from international society, conference, symposium, etc.  Country:Japan

  • 奨励発表賞

    2018.12   情報処理学会  

    本田 佳鈴,他

     More details

    Award type:Award from Japanese society, conference, symposium, etc.  Country:Japan

  • 奨励発表賞

    2018.11   情報処理学会  

    臼崎 翔太郎,他

     More details

    Award type:Award from Japanese society, conference, symposium, etc.  Country:Japan

  • Best Paper Award

    2017.8   NBiS-2017  

    臼崎 翔太郎,他

     More details

    Award type:Award from international society, conference, symposium, etc.  Country:Japan

Grant-in-Aid for Scientific Research 【 display / non-display

  • AIによって高度化されたサイバー攻撃に対抗する次世代クラウドセキュリティ基盤の構築

    Grant number:24K14917  2024.04 - 2027.03

    独立行政法人日本学術振興会  科学研究費補助金  基盤研究(C)

      More details

    Authorship:Principal investigator 

  • クラウドサービスに対する大規模な分散型攻撃の検知とその規模の縮小化に関する研究

    Grant number:21K11849  2021.04 - 2024.03

    独立行政法人日本学術振興会  科学研究費補助金  基盤研究(C)

      More details

    Authorship:Principal investigator 

  • クラウドサービスに対する経済的な損失を目的にしたEDoS攻撃の検知に関する研究

    Grant number:18K11268  2018.04 - 2023.03

    独立行政法人日本学術振興会  科学研究費補助金  基盤研究(C)

      More details

    Authorship:Principal investigator 

  • 深層学習を用いた筋電位による多要素個人認証の複数点測定による高精度化

    Grant number:24K14948  2024.04 - 2027.03

    独立行政法人日本学術振興会  科学研究費補助金  基盤研究(C)

      More details

    Authorship:Coinvestigator(s) 

  • DXの急展開に対応する超強靭なパスワード・リスト攻撃防止基盤の確立

    Grant number:22K12013  2022.04 - 2025.03

    独立行政法人日本学術振興会  科学研究費補助金  基盤研究(C)

      More details

    Authorship:Coinvestigator(s) 

display all >>

Available Technology 【 display / non-display