{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T13:31:07Z","timestamp":1760707867308},"reference-count":8,"publisher":"World Scientific Pub Co Pte Lt","issue":"06","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[2007,9]]},"abstract":"<jats:p> In offline handwritten character recognition, the classifier with modified quadratic discriminant function (MQDF) has achieved good performance. The parameters of MQDF classifier are commonly estimated by the maximum likelihood (ML) estimator, which maximizes the within-class likelihood instead of directly minimizing the classification errors. To improve the performance of MQDF classifier, in this paper, the MQDF parameters are revised by discriminative training using a minimum classification error (MCE) criterion. The proposed algorithm is applied to recognizing handwritten numerals and handwritten Chinese characters, the recognition rates obtained are among the highest that have ever been reported. <\/jats:p>","DOI":"10.1142\/s0218001407005776","type":"journal-article","created":{"date-parts":[[2007,9,19]],"date-time":"2007-09-19T09:42:29Z","timestamp":1190194949000},"page":"1035-1046","source":"Crossref","is-referenced-by-count":5,"title":["DISCRIMINATIVE TRAINING BASED QUADRATIC CLASSIFIER FOR HANDWRITTEN CHARACTER RECOGNITION"],"prefix":"10.1142","volume":"21","author":[{"given":"RUI","family":"ZHANG","sequence":"first","affiliation":[{"name":"State Key Laboratory of Intelligent Technology and Systems, Department of Electronic Engineering, Tsinghua University, Beijing, P. R. China"}]},{"given":"XIAO QING","family":"DING","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Intelligent Technology and Systems, Department of Electronic Engineering, Tsinghua University, Beijing, P. R. China"}]},{"given":"HAI LONG","family":"LIU","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Intelligent Technology and Systems, Department of Electronic Engineering, Tsinghua University, Beijing, P. R. China"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"reference":[{"key":"rf2","doi-asserted-by":"publisher","DOI":"10.1023\/A:1012454411458"},{"key":"rf4","doi-asserted-by":"publisher","DOI":"10.1109\/5.726793"},{"key":"rf6","first-page":"149","volume":"9","author":"Kimura F.","journal-title":"IEEE Trans. Patt. Anal. Mach. Intell."},{"key":"rf7","doi-asserted-by":"publisher","DOI":"10.1016\/S0031-3203(96)00153-7"},{"key":"rf8","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"rf9","first-page":"1097","volume":"7","author":"Michael D. G.","journal-title":"IEEE Trans. Imag. Process."},{"key":"rf11","unstructured":"B.\u00a0Sch\u00f6lkopf, Advances in Neural Information Processing Systems (MIT Press, Cambridge, 1998)\u00a0pp. 640\u2013646."},{"key":"rf12","doi-asserted-by":"publisher","DOI":"10.1002\/1098-1098(2000)11:3<181::AID-IMA1003>3.0.CO;2-E"}],"container-title":["International Journal of Pattern Recognition and Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0218001407005776","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,7]],"date-time":"2019-08-07T02:20:19Z","timestamp":1565144419000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0218001407005776"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2007,9]]},"references-count":8,"journal-issue":{"issue":"06","published-online":{"date-parts":[[2011,11,21]]},"published-print":{"date-parts":[[2007,9]]}},"alternative-id":["10.1142\/S0218001407005776"],"URL":"https:\/\/doi.org\/10.1142\/s0218001407005776","relation":{},"ISSN":["0218-0014","1793-6381"],"issn-type":[{"value":"0218-0014","type":"print"},{"value":"1793-6381","type":"electronic"}],"subject":[],"published":{"date-parts":[[2007,9]]}}}