HOSHINO Yukinobu

ホシノユキノブ | HOSHINO Yukinobu

Affiliation and department：
Job title： Professor
Homepage URL (2)： https://www.kochi-tech.ac.jp/profile/ja/hoshino-yukinobu.html , https://www.kochi-tech.ac.jp/profile/en/hoshino-yukinobu.html

Research field (4)： Intelligent informatics , Soft computing , Intelligent robotics , Human interfaces and interactions

Research keywords (19)：感性情報処理 , 感性工学 , ヒューマンインタフェース , ゲーミング , マルチエージェント , ロボカップ , 機械学習 , 知的画像処理 , 知能システム , ソフトコンピューティング , ファジィ , PLD , FPGA , Image sensing , Neural Network , Fuzzy , SOFT computing , Machine Learning , Intelligent system

Research theme for competitive and other funds (8)：

2024 - 2027 Cascaded-ANFISと機械学習による長期的な降雨-流出予測の実現可能性の検証
2022 - 2025 Establishment of AI forecasting technology for the dam storage volume, rainfall, and river flow in Japan and other Asian countries
2017 - 2018 大豊町における害獣対策のための害獣捕獲システムの研究
2013 - 2016 Space operation system development for cognitive exercise therapy rehabilitation
2013 - 2016 FPGA技術を用いたリアルタイム高速処理技術を用いた認知運動療法に基づくハビリテーションゲーム空間開発

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Papers (96)：

Sanjit Kumar, Mayank Agarwal, Vishal Deshpande, James R. Cooper, Khabat Khosravi, Namal Rathnayake, Yukinobu Hoshino, Komali Kantamaneni, Upaka Rathnayake. AI-driven predictions of geophysical river flows with vegetation. Scientific Reports. 2024
Yukinobu Hoshino, Yuka Nishiyama, Toshimi Yamamoto, Yuki Shinomiya, Namal Rathnayake, Tuan Linh Dang. Human-inspired similarity control system: Enhancing line-following robot perception. Applied Soft Computing. 2024
Sherin Kularathne, Namal Rathnayake, Madhawa Herath, Upaka Rathnayake, Yukinobu Hoshino. Impact of economic indicators on rice production: A machine learning approach in Sri Lanka. PLOS ONE. 2024
Mampitiya, L., Rathnayake, N., Hoshino, Y., Rathnayake, U. Performance of machine learning models to forecast PM10 levels. MethodsX. 2024. 12
Lakindu Mampitiya, Kenjabek Rozumbetov, Namal Rathnayake, Valery Erkudov, Adilbay Esimbetov, Shanika Arachchi, Komali Kantamaneni, Yukinobu Hoshino, Upaka Rathnayake. Artificial intelligence to predict soil temperatures by development of novel model. Scientific Reports. 2024. 14. 1

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MISC (102)：

Design the convolutional layer synchronizing camera signals using Verilog HDL and evaluated the latency of processing time. 2021. 32. 8. 8-15
山田耕一, 星野孝総, 藤本勝成. FSS2020 開催報告. 知能と情報. 2021. 33. 1. 26-27
三谷慶太, 星野孝総. Development and Evaluation of a Learning Level Prediction Model Based on the Growth Curve About the Long-Term Learners. 知能と情報(CD-ROM). 2021. 33. 4
Kusunose Shoya, Shinomiya Yuki, Ushiwaka Takashi, Maeda Nagamasa, Hoshino Yukinobu. Improving the Preciseness of Single Selection of Neighboring Cells in Immune Cell Selection using Partial Weighting. Proceedings of the Fuzzy System Symposium. 2021. 37. 231-234
Dohi Naoki, Hoshino Yukinobu. The usefulness of forecasting confirmed cases of the novel coronavirus with statistical and neural network models. Proceedings of the Fuzzy System Symposium. 2021. 37. 227-230

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Professional career (1)：

博士(工学) (立命館大学)

Work history (5)：

2024/07 - 現在 Kochi University of Technology School of Systems Engineering, Data & Innovation Professor
2008/04 - 2024/06 高知工科大学システム工学群電子・光システム工学教室准教授
2006/04 - 2008/03 高知工科大学工学部電子・光システム工学科助教授
2002/04 - 2006/03 立命館大学情報理工学部知能情報学科講師
2000/04 - 2002/03 立命館大学リサーチアシスタント

Association Membership(s) (9)：

電子情報通信学会 , 進化計算学会 , ゲーミング&シミュレーション学会 , ヒューマンインタフェース学会 , 日本感性工学会 , 計測自動制御学会 , システム制御情報学会 , 日本知能情報ファジィ学会 , IEEE

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