Verification of the Effectiveness of the Online Tuning System for Unknown Person in the Awaking Behavior Detection System

  • Authors:

  • Hironobu Satoh;Fumiaki Takeda

  • Affiliations:

  • Kochi University of Technology, Japan;Kochi University of Technology, Japan

  • Venue:
  • IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part II: Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living
  • Year:
  • 2009

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Abstract

We have developed an awaking behavior detection system using a neural network (abbreviated as NN). However, the detection ability of unknown people is not sufficient with compared to that of learned people. In this research, to improve the detection ability of unknown people, we apply an online tuning system using a continuous learning of the NN for the detection system. In the online tuning system, only a few additional data of a new objective person are used for the continuous learning, where the weights of the NN converged in the initial learning are used as the initial weights for the continuous learning. In this paper, to verify an ability of the online tuning system, we compare detection ability of the converged initial learning with that of the converged online tuning.