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. |
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1.–5. rezultāts no 84.
25. lappuse
... shown in Fig.2.3 and the new data is as in Fig.4.5. Because of the stroke connection in Fig. 4.5 which is not present in Fig2.3, the two data sets result in different number of states, which gives rise to a difficulty in learning. Our ...
... shown in Fig.2.3 and the new data is as in Fig.4.5. Because of the stroke connection in Fig. 4.5 which is not present in Fig2.3, the two data sets result in different number of states, which gives rise to a difficulty in learning. Our ...
37. lappuse
... shown here represent percent difference in error rate relative to the baseline: overall basic-test character error when the system is trained on T1. Training Text Lowercase | Uppercase Digits Symbols T1 +7 +106 –27 +139 BT / CT –6/–2 ...
... shown here represent percent difference in error rate relative to the baseline: overall basic-test character error when the system is trained on T1. Training Text Lowercase | Uppercase Digits Symbols T1 +7 +106 –27 +139 BT / CT –6/–2 ...
43. lappuse
... shown in Figure 3 (a). 2 Z & × N. N. > * Z. > * * no - T - Y 2 - T - N. 2 : \ / \ s y <2. / 7 × (a) Relaxed versions of “T” as a result (b) Relaxed versions of “T” as a result of applying type deformations of applying directional ...
... shown in Figure 3 (a). 2 Z & × N. N. > * Z. > * * no - T - Y 2 - T - N. 2 : \ / \ s y <2. / 7 × (a) Relaxed versions of “T” as a result (b) Relaxed versions of “T” as a result of applying type deformations of applying directional ...
46. lappuse
... shown below: Pairs Triples All models share (C, c), (O, o], (P,p), (S, s), T nil the same structure(s) |_(V, v), (W, w), (X,x) Some models share (M, m), (U, u), (Y, y) (I, 1, 1), the same structure(s) (O, o, 0) In general ...
... shown below: Pairs Triples All models share (C, c), (O, o], (P,p), (S, s), T nil the same structure(s) |_(V, v), (W, w), (X,x) Some models share (M, m), (U, u), (Y, y) (I, 1, 1), the same structure(s) (O, o, 0) In general ...
50. lappuse
... shown. In (b) the same image has been divided into a sequence of basic ink units (i.e., “strokes”) Y = y1, y2, ..., y15. In (c) the corresponding list of (two) potential diacriticals. 1.1 Previous Approaches Recognition systems using a ...
... shown. In (b) the same image has been divided into a sequence of basic ink units (i.e., “strokes”) Y = y1, y2, ..., y15. In (c) the corresponding list of (two) potential diacriticals. 1.1 Previous Approaches Recognition systems using a ...
Saturs
17 | |
HANDWRITTEN FORM PROCESSING | 79 |
HANDWRITTEN WORD RECOGNITION | 151 |
SEGMENTATION | 223 |
ORIENTAL SCRIPT PROCESSING | 275 |
NUMERAL RECOGNITION | 357 |
EMERGING TECHNIQUES | 437 |
APPLICATIONS | 517 |
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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