A study on total optimization of multiple pattern recognition systems using cooperative and adaptive training

2015 Fiscal Year Final Research Report

• Project/Area Number: 25330207
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Perceptual information processing
• Research Institution: Waseda University
• Principal Investigator: Ogawa Tetsuji 早稲田大学, 理工学術院, 准教授 (70386598)
• Project Period (FY): 2013-04-01 – 2016-03-31
• Keywords: パターン認識 / 性能予測 / 深層学習 / 全体最適化

Outline of Final Research Achievements

Attempts have been made to cooperatively optimize multiple pattern recognition systems, developing a total system efficiently and automatically. Specifically, the clustering technique that is robust against the environmental changes and multistream pattern recognition framework, which cooperatively exploits information yielded from multiple systems, have been developed as the fundamental technologies for adaptively refining the systems to cope with the changes in characteristics of data (e.g., users and surrounding environments of the system).

Free Research Field

知覚情報処理