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Graphical Item Recognition Using Neural Networks (1998)  (Make Corrections)  
Sheng Jianqing



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Abstract: ency graph representations of handwritten digits can be used for learning and classification. Preliminary results show the good generalization capability of recursive network. A hybrid system architecture is proposed in order that autoassociator-based networks and recursive neural networks can be integrated in an appropriate way. Clustering of classes under consideration can be achieved based on structured representations. Thus, the number of underlying classes can be reduced to facilitate... (Update)

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BibTeX entry:   (Update)

@misc{ jianqing-graphical,
  author = "Sheng Jianqing",
  title = "Graphical Item Recognition Using Neural Networks",
  url = "citeseer.ist.psu.edu/jianqing98graphical.html" }
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