• DocumentCode
    457361
  • Title

    Comparative Classifier Aggregation

  • Author

    Abdulkader, Ahmad ; Drakopoulos, John A. ; Zhang, Qi

  • Author_Institution
    Tablet PC Handwriting Recognition Group, Microsoft Corp., Redmond, WA
  • Volume
    3
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    156
  • Lastpage
    159
  • Abstract
    Comparative neural networks are a new kind of neural networks that can be used to compare two or more items given a set of context features. They compare two items at a time indicating the one that matches the context features better. Consequently, any sorting algorithm, coupled with such a neural comparator, can sort any set of items. Although applications include ink segmentation (for handwriting recognition purposes) and Web page ranking, our emphasis on this paper is on classifier aggregation and, in particular, the integration of our standard handwriting recognizers with a user personalization database that consists of user samples
  • Keywords
    handwriting recognition; handwritten character recognition; neural nets; pattern classification; comparative classifier aggregation; comparative neural network; context feature matching; handwriting recognition; handwriting recognizer; item comparison; item sorting; neural comparator; user personalization database; Aggregates; Convergence; Databases; Handwriting recognition; Ink; Neural networks; Pattern recognition; Sorting; Training data; Web pages;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-2521-0
  • Type

    conf

  • DOI
    10.1109/ICPR.2006.388
  • Filename
    1699491