相関情報抽出ネットと空間認識能力の教師なし学習  [in Japanese] Unsupervised Learning of the Spatial Recognition Ability Using the Correlated Information Extracting Neural Network  [in Japanese]

Access this Article

Search this Article

Author(s)

Abstract

The Correlated Information Extracting Neural Network has been proposed to extract the common information among multiple kinds of inputs. Applying this neural network to a robot with a visual sensor, the distance to an object could be extracted as the correlated information between motional signals and visual signals after learning. In the case of stereo vision which uses two visual sensors, the output representing the distance, did not depend on the size of the object. When the signals of tactile sensor were added to the neural network, the robot could detect from the visual signals or from the motional signals if the robot touched the object.

Journal

  • The Brain & Neural Networks

    The Brain & Neural Networks 3(1), 11-16, 1996-03-05

    Japanese Neural Network Society

References:  15

Cited by:  2

Codes

  • NII Article ID (NAID)
    10008841111
  • NII NACSIS-CAT ID (NCID)
    AA11658570
  • Text Lang
    JPN
  • Article Type
    Journal Article
  • ISSN
    1340766X
  • Data Source
    CJP  CJPref  J-STAGE 
Page Top