Design compact recognizers of handwritten Chinese characters using precision constrained Gaussian models, minimum classification error training and parameter compression

Proceedings of the International Conference on Document Analysis and Recognition, ICDAR

Volumn , Issue , 2009, Pages 36-40

  Wang, Yongqiang ^a,b   Huo, Qiang ^a  

^a MICROSOFT RESEARCH ASIA   (China)

^b UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

[No Author keywords available]

Indexed keywords

ASIAN LANGUAGES; CHARACTER MODELING; ESTIMATE MODEL; GAUSSIAN MODEL; HANDWRITING RECOGNITION; HANDWRITTEN CHINESE CHARACTER; MINIMUM CLASSIFICATION ERROR; MINIMUM CLASSIFICATION ERROR TRAINING; MODEL PARAMETERS; MODIFIED QUADRATIC DISCRIMINANT FUNCTIONS; RECOGNITION ACCURACY; SPLIT VECTOR QUANTIZATION; TRAINING DATA; TRAINING PROCEDURES;

CLASSIFIERS; DATA COMPRESSION; FEEDFORWARD NEURAL NETWORKS; LEARNING SYSTEMS; MAXIMUM LIKELIHOOD ESTIMATION; OPTICAL CHARACTER RECOGNITION;

VECTOR QUANTIZATION;

EID: 71249143926     PISSN: 15205363     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDAR.2009.41     Document Type: Conference Paper

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