Scene Memory on Competitively Growing Neural Network Using Temporal Coding: Self-organized Learning and Glance Recognizability

  • Masayasu Atsumi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3316)

Abstract

We have been building the competitively growing neural network using temporal coding for quick one-shot object learning and glance object recognition, which is the core of our saliency-based scene memory model. This neural network represents objects using latency-based temporal coding and grows size and recognizability through learning and self-organization. This paper shows that self-organized learning is quickly performed and glance recognition is successfully performed by our model through simulation experiments of a robot equipped with a camera.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Masayasu Atsumi
    • 1
  1. 1.Dept. of Information Systems Sci, Faculty of Eng.Soka UniversityTokyoJapan

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