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亀山 啓輔

Kameyama, Keisuke

システム情報系 , 教授
Institute of Systems and Information Engineering , Professor

http://adapt.cs.tsukuba.ac.jp

社会を支える基盤技術の ブレイクスルーを目指す
パターン認識・機械学習リサーチユニット
To achieve a breakthrough for the development of basic technologies to support society

2017-02-21

福井 和広 亀山 啓輔 佐久間 淳 滝沢 穂高 鈴木 健嗣
人と機械のコラボレーションの実現を目指す
人間行動支援リサーチユニット
For Collaboration between People and Machines

2015-03-16

伊藤 誠 遠藤 靖典 亀山 啓輔 福井 和広
オープンアクセス版の論文は「つくばリポジトリ」で読むことができます。
  1. 1. Physics-Informed Antisymmetric Recurrent Neural Networks for Solving Nonlinear Partial Differential Equations Maniamfu, Pavodi; Ali, U. A. Md. Ehsan; Sakai, Ko; Kameyama, Keisuke
      Neural Information Processing. ICONIP 2024. Lecture Notes in Computer Science 15289: (2025)
  2. 2. Inheritance of Attention Region in Model Compression by Distillation in Image Classification Shirahama, Takumi; Kameyama, Keisuke
      AICCC '24 Proceedings of the 2024 7th Artificial Intelligence and Cloud Computing Conference (2025)
  3. 3. Anomaly Detection in IoT Computing Platform Using Self-Timed Data-Driven Processor MAEDA, Hajime; SANNOMIYA, Shuji; KAMEYAMA, Keisuke; TAKIZAWA, Hotaka (+1 著者) NISHIKAWA, Hiroaki
      IEEE 15th Annual Computing and Communication Workshop and Conference (CCWC) 00901 (2025)
  4. 4. Efficient band reduction for hyperspectral imaging with dependency-based segmented principal component analysis Ali; U. A. Md. Ehsan; Maniamfu, Pavodi; Kameyama, Keisuke
      INTERNATIONAL JOURNAL OF REMOTE SENSING 45: 9311 (2024)
  5. 5. Affinity-Weighted RandAugment for Problem-Oriented Augmentation in Image Classification PARK, Yuna; TAKASE, Tomoumi; KAMEYAMA, Keisuke; ONISHI, Masaki
      Proceedings of International Joint Conference on Neural Networks 2024 1 (2024)
  6. 6. PINN with Antisymmetric RNN for Solving Nonlinear Partial Differential Equations Maniamfu; Pavodi Ndoyi; Ali, U. A. Md. Ehsan; Kameyama, Keisuke
      International Conference on Scientific Computation and Machine Learning 2024 (2024)
  7. 7. LSTM-based Forecasting using Policy Stringency and Time-varying Parameters of the SIR Model for COVID-19 Maniamfu; Pavodi Ndoyi; Kameyama, Keisuke
      2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA) 111 (2023)
  8. 8. Machine Learning Curriculums Generated by Classifier Ensembles Huang, Tzu-Jui; Kameyama, Keisuke
      2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA) 117 (2023)
  9. 9. CNN Model Compression by Merit-Based Distillation Morikawa, Takumi; Kameyama, Keisuke
      2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA) 122 (2023)
  10. 10. Informative Band Subset Selection for Hyperspectral Image Classification using Joint and Conditional Mutual Information Ali; U. A. Md Ehsan; Kameyama, Keisuke
      IEEE Symposium on Computational Intelligence in Remote Sensing (IEEE SSCI 2022) 573 (2022)
  11. 11. Joint-Conditional Mutual Information based Feature Subset Selection for Remotely Sensed Hyperspectral Image Classification Ali; U. A. Md Ehsan; Kameyama, Keisuke
      Technical Report of IEICE 122: 115 (2022)
  12. 12. Multi-Stage Model Compression using Teacher Assistant and Distillation with Hint-Based Training Morikawa, Takumi; Kameyama, Keisuke
      2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) 484 (2022)
  13. 13. Adaptive Selection of Classifiers for Person Recognition by Iris Pattern and Periocular Image Ogawa, Keita; Kameyama, Keisuke
      Neural Information Processing. ICONIP 2021. Lecture Notes in Computer Science 13111: 656 (2021)
  14. 14. 虹彩認証における高次スペクトル特徴量の利用 亀山, 啓輔
      Technical Report of IEICE 121: 31 (2021)
  15. 15. Pre-Training Acquisition Functions by Deep Reinforcement Learning for Fixed Budget Active Learning Taguchi, Yusuke; Hino, Hideitsu; Kameyama, Keisuke
      Neural Processing Letters 53: 1945 (2021) Semantic Scholar
  16. 16. 異なる倍率の走査型電子顕微鏡像を用いた金属材料の解析 伊藤, 龍之介; 亀山, 啓輔; 日野, 英逸
      電子情報通信学会技術研究報告 (信学技報) 119: 71 (2020)
  17. 17. 強化学習を用いた複数データ選択のための能動学習 田口, 優介; 日野, 英逸; 亀山, 啓輔
      Technical Report of IEICE 119: 99 (2020)
  18. 18. CNNを用いた低解像度虹彩画像からの認証特徴量予測 渡邉, 崚; 亀山, 啓輔
      Technical Report of IEICE 119: 5 (2019)
  19. 19. Active Learning with Interpretable Predictor Taguchi, Yusuke; Kameyama, Keisuke; Hino, Hideitsu
      Proceedings of International Joint Conference on Neural Networks (IJCNN) 1 (2019) Semantic Scholar
  20. 20. Parallel Cooperative Ensemble Learning by Adaptive Data Weighting and Error-Correcting Output Codes Utsumi, Shota; Kameyama, Keisuke
      Lecture Notes in Computer Science (Proc. ICONIP 2018) 11303: 673 (2018)
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  1. 1. リスク工学の視点とアプローチ ―現代生活に潜むリスクにどう取り組むかー 古川宏; 佐藤美佳; 亀山啓輔; 谷口綾子; 梅本通孝; 羽田野祐子
    コロナ社 2009年1月
  2. 2. Model Switching Maneuvers in Pattern Recognition Systems Kameyama, Keisuke
    1999年9月

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