Advances In Handwriting RecognitionSeong-whan Lee World Scientific, 1999. gada 1. jūn. - 600 lappuses Advances in Handwriting Recognition contains selected key papers from the 6th International Workshop on Frontiers in Handwriting Recognition (IWFHR '98), held in Taejon, Korea from 12 to 14, August 1998. Most of the papers have been expanded or extensively revised to include helpful discussions, suggestions or comments made during the workshop. |
No grāmatas satura
1.–5. rezultāts no 83.
x. lappuse
... Performance of Polynomial Classifiers by Iterative Learning...... 378 J. Franke Distinctiveness and Similarities of ... Performance Comparison of Statistical and Neural Network Classifiers in Handwritten Digits Recognition ...
... Performance of Polynomial Classifiers by Iterative Learning...... 378 J. Franke Distinctiveness and Similarities of ... Performance Comparison of Statistical and Neural Network Classifiers in Handwritten Digits Recognition ...
4. lappuse
... performance achieved by these systems at that time, less research on handwriting recognition took place during the eighties”. The first research works dealt with the recognition of isolated handprinted characters”. These works followed ...
... performance achieved by these systems at that time, less research on handwriting recognition took place during the eighties”. The first research works dealt with the recognition of isolated handprinted characters”. These works followed ...
5. lappuse
... performance of such systems is mainly determined by the performance of the worst module. In this paper, we consider the following questions: is there only the PR as possible framework? Is it possible to design systems using less ...
... performance of such systems is mainly determined by the performance of the worst module. In this paper, we consider the following questions: is there only the PR as possible framework? Is it possible to design systems using less ...
13. lappuse
... performance. 5 Conclusion, Future Trends and Outlook The approach suggested might be summarized as follows: use the optimal information amount to solve the problem (i.e suppress all the unnecessary information); use the local visual ...
... performance. 5 Conclusion, Future Trends and Outlook The approach suggested might be summarized as follows: use the optimal information amount to solve the problem (i.e suppress all the unnecessary information); use the local visual ...
28. lappuse
... performance may be possible by exploiting grammatical structure associated with character sequence instead of individual characters. This is one of the challenging future projects. References 1. L.R.Rabiner: “A Tutorial on Hidden Markov ...
... performance may be possible by exploiting grammatical structure associated with character sequence instead of individual characters. This is one of the challenging future projects. References 1. L.R.Rabiner: “A Tutorial on Hidden Markov ...
Saturs
17 | |
HANDWRITTEN FORM PROCESSING | 79 |
HANDWRITTEN WORD RECOGNITION | 151 |
SEGMENTATION | 223 |
ORIENTAL SCRIPT PROCESSING | 275 |
NUMERAL RECOGNITION | 357 |
EMERGING TECHNIQUES | 437 |
APPLICATIONS | 517 |
Citi izdevumi - Skatīt visu
Bieži izmantoti vārdi un frāzes
algorithm applied approach B-spline bankcheck bigram character candidates character line character recognition character segmentation classifier combination computed connected components contour corresponding courtesy amount database described detected diacriticals dictionary digit distance error rate evaluation example experimental results experiments feature extraction feature set feature vectors Figure function fuzzy graph grapheme handwriting recognition handwritten character handwritten numerals handwritten words Hidden Markov Models horizontal Hough transform hypotheses integrated Kanji learning legal amount letters lexicon line segments matching matrix nat-ja neural network node obtained off-line on-line handwriting recognition optimal output paper parameters Pattern Recognition performance pixels points preprocessing probability problem Proc proposed method prototype quantization recognition rate recognition results recognition system recognizer samples sequence shown speech recognition step string stroke structure Suen Table technique template threshold touching type vector quantizer wavelet word recognition writing