木構造を有する階層型確率ニューラルネットの提案と指形状識別への応用
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概要
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This paper proposes a new pattern classification method using probabilistic neural networks with hie rarchical structure. In this method, a log-linearized Gaussian mixture networkas a probabilistic neural networki sused at each node of a herarchical classification tree. The method proposed here automatically constructs a tree of neural networks from given data, and can achieve suitable discrimination. Also, Cross-validation for a constructed neural tree can improve the generalization ability for discrimination of unlearned dat a. Validity of the proposed method is demonstrated with discrimnation of hand shape.
- 公益社団法人 計測自動制御学会の論文
著者
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村上 樹里
Hiroshima Univ., Faculty of Engineering, Kagamiyama
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岡本 勝
Hiroshima Univ., Faculty of Engineering, Kagamiyama
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柴 建次
Hiroshima Univ., Faculty of Engineering, Kagamiyama
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辻 敏夫
Hiroshima Univ., Faculty of Engineering, Kagamiyama