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 77.
v. lappuse
... experimental results. According to the main topics of the handwriting recognition research, the contributed papers of this special book edition are organized into nine sections: Part 1: The State of the Art in Handwriting Recognition ...
... experimental results. According to the main topics of the handwriting recognition research, the contributed papers of this special book edition are organized into nine sections: Part 1: The State of the Art in Handwriting Recognition ...
26. lappuse
... results in a quite satisfactory criterion (4.3.13) for model generation. (ii) The above procedure designates that if ... Experiment Database Kuchibue contains Kanji, Hiragana, Katakana, Western alphabets, numerals and symbols. In our ...
... results in a quite satisfactory criterion (4.3.13) for model generation. (ii) The above procedure designates that if ... Experiment Database Kuchibue contains Kanji, Hiragana, Katakana, Western alphabets, numerals and symbols. In our ...
39. lappuse
... Experimental results show that the recognition rates are 98.60% for digits, 98.49% for uppercase letters, 97.44% for lowercase letters, and 97.40% for the combined set. When the rejected cases are excluded from the calculation, the ...
... Experimental results show that the recognition rates are 98.60% for digits, 98.49% for uppercase letters, 97.44% for lowercase letters, and 97.40% for the combined set. When the rejected cases are excluded from the calculation, the ...
40. lappuse
... experimental results, which are then followed by some concluding remarks. 2 Related Work Using the structural approach, two-dimensional patterns, such as characters, can be represented in at least two different ways. The first one is to ...
... experimental results, which are then followed by some concluding remarks. 2 Related Work Using the structural approach, two-dimensional patterns, such as characters, can be represented in at least two different ways. The first one is to ...
44. lappuse
... = h9 WThreshold HDiff=ha - ht if (HDiff > MinDiff) then Result = 'y' else Result = 'u' h2 Figure 5: Outline of an algorithm for distinguishing between 'u' and “y” 7 Experimental Results In our experiment, we used an on-line. 44.
... = h9 WThreshold HDiff=ha - ht if (HDiff > MinDiff) then Result = 'y' else Result = 'u' h2 Figure 5: Outline of an algorithm for distinguishing between 'u' and “y” 7 Experimental Results In our experiment, we used an on-line. 44.
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