کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
531080 869808 2013 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A discriminative linear regression approach to adaptation of multi-prototype based classifiers and its applications for Chinese OCR
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
A discriminative linear regression approach to adaptation of multi-prototype based classifiers and its applications for Chinese OCR
چکیده انگلیسی

This paper presents a new discriminative linear regression approach to adaptation of a discriminatively trained prototype-based classifier for Chinese OCR. A so-called sample separation margin based minimum classification error criterion is used in both classifier training and adaptation, while an Rprop algorithm is used for optimizing the objective function. Formulations for both model-space and feature-space adaptation are presented. The effectiveness of the proposed approach is confirmed by a series of experiments for adaptation of font styles and low-quality text, respectively.


► We have proposed a new SSM-MCE linear regression approach to adaptation of an SSM-MCE trained prototype-based classifier.
► Rprop optimization for both SSM-MCE training and adaptation.
► Formulations for both model-space and feature-space adaptation are presented.
► Experiments show our approach achieves significant improvements over state-of-the-art.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 46, Issue 8, August 2013, Pages 2313–2322
نویسندگان
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