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  • 标题:多重構造ニューラルネットワークを用いた車載センサ情報統合に基づく車種認識
  • 本地全文:下载
  • 作者:鄭 明 ; 後藤 敏行 ; 下村 倫子
  • 期刊名称:映像情報メディア学会誌
  • 印刷版ISSN:1342-6907
  • 电子版ISSN:1881-6908
  • 出版年度:2005
  • 卷号:59
  • 期号:4
  • 页码:621-628
  • DOI:10.3169/itej.59.621
  • 出版社:The Institute of Image Information and Television Engineers
  • 摘要:An algorithm of vehicle type recognition integrating on-board sensor information is proposed. This method, compensates for apparent size differences due to the objective distances of on-board sensors, the distance and intensity detected by a scanning laser radar, and the images input from an on-board CCD camera. A frame recognition which consists of a multiplex structured neural network using the three kinds of adjusted data is performed, then the results are integrated to improve the accuracy of the recognition of each object. Experiments using road images captured while driving and the sensing data show that this method is effective : average recognition rates were above 96.1% for various road environments.
  • 关键词:車載センサ情報統合;多重構造ニューラルネットワーク;適応テンプレートマッチング;時系列観測;車両認識
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