The impact of large training sets on the recognition rate of off-line Japanese Kanji character classifiers

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2423, Issue , 2002, Pages 106-110

  Velek, Ondrej ^a   Nakagawa, Masaki ^a  

^a TOKYO UNIVERSITY OF AGRICULTURE AND TECHNOLOGY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFIERS;

CHARACTER PATTERNS; COMPUTING POWER; KANJI CHARACTERS; LARGE DATASETS; NUMBER OF SAMPLES; TRAINING SAMPLE; TRAINING SETS;

CLASSIFICATION (OF INFORMATION);

EID: 84947741610     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45869-7_13     Document Type: Conference Paper

References (6)

1. T. Kawatani, H. Shimizu; Handwritten Kanji Recognition with the LDA Method, Proc. 14th ICPR, Brisbane, 1998, Vol.II, pp.1031-1035
2. M. Nakagawa, et al., On-line character pattern database sampled in a sequence of sentences without any writing instructions, Proc. 4th ICDAR, 1997, pp.376-380.
3. S. Jaeger, M. Nakagawa, Two on-line Japanese character databases in Unipen format, Proc. 6th ICDAR, Seattle, 2001, pp.566-570.
4. K. Matsumoto, T. Fukushima, M. Nakagawa, Collection and analysis of on-line handwritten Japanese character patterns, Proc. 6th ICDAR, Seattle, 2001, pp.496-500.
5. O. Velek, Ch.Liu, M. Nakagawa, Generating Realistic Kanji Character Images from Online Patterns, Proc. 6th ICDAR, pp.556-560, 2001
6. O. Velek, Ch.Liu, S.Jaeger, M.Nakagawa, An Improved Approach to Generating Realistic Kanji Character Images and its Effect to Improve Off-line Recognition Performance, accepted for ICPR 2002.