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@TECHREPORT{breuel-93.02,
         author = {Breuel, Thomas M.},
       projects = {Idiap},
          title = {Recognition of Handprinted Digits},
           type = {Idiap-RR},
         number = {Idiap-RR-06-1993},
           year = {1993},
    institution = {IDIAP},
       abstract = {This paper describes a system that recognizes hand-printed digits. The system is based on optimal bounded error matching, a technique already in common use in general-purpose 2D and 3D visual object recognition systems in cluttered, noisy scenes. In this paper, we demonstrate that the same techniques achieve high recognition rates (up to 99.2\%) on real-world data (the NIST database of hand-printed census forms and the CEDAR database of digits extracted from U.S. mail ZIP codes). As part of the system, we describe a post-processing step for $k$-nearest neighbor classifiers based on decision trees that can be used (in place of the usual heuristic methods) for setting thresholds and improves recognition rates significantly.},
            pdf = {https://publications.idiap.ch/attachments/reports/1993/93-06.pdf},
     postscript = {ftp://ftp.idiap.ch/pub/reports/1993/93-06.ps.gz},
ipdmembership={vision},
}