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

この論文にアクセスする

この論文をさがす

著者

抄録

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.

収録刊行物

  • 日本神経回路学会誌 = The Brain & neural networks

    日本神経回路学会誌 = The Brain & neural networks 3(1), 11-16, 1996-03-05

    日本神経回路学会

参考文献:  15件中 1-15件 を表示

被引用文献:  2件中 1-2件 を表示

各種コード

  • NII論文ID(NAID)
    10008841111
  • NII書誌ID(NCID)
    AA11658570
  • 本文言語コード
    JPN
  • 資料種別
    ART
  • ISSN
    1340766X
  • データ提供元
    CJP書誌  CJP引用  J-STAGE 
ページトップへ