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 58.
23. lappuse
... Equation (3.2.1) forces Q(T) to be the final state qn of 7t(“ji”), which significantly reduces erroneous recognition ... compute ar IIlax P({O(t)}{ , | H 4.0.1 *te,).sos.) ({O(t)}_1 | ?t) (4.0.1) with N fixed. The efficiency of this ...
... Equation (3.2.1) forces Q(T) to be the final state qn of 7t(“ji”), which significantly reduces erroneous recognition ... compute ar IIlax P({O(t)}{ , | H 4.0.1 *te,).sos.) ({O(t)}_1 | ?t) (4.0.1) with N fixed. The efficiency of this ...
25. lappuse
... compute n(Oc, q,), n(Oc, qi, vis) and n(Oc, qi, v21), c = 2, ..., C as in Step 1.2. If one applies the procedure described in Stepl.1 to the data given in Fig. 4.5, then one obtains (1,5),(1,5),(1,5) (1,15),(1,15),(1,15),(1 ...
... compute n(Oc, q,), n(Oc, qi, vis) and n(Oc, qi, v21), c = 2, ..., C as in Step 1.2. If one applies the procedure described in Stepl.1 to the data given in Fig. 4.5, then one obtains (1,5),(1,5),(1,5) (1,15),(1,15),(1,15),(1 ...
26. lappuse
... compute — log P({O1(t)}=1, Q(T.) = qx (H1) | ?ti) where Q(T.) = q.v.(?(1), i.e., QN is obtained from hti. We observed that the length of sequence {O(t)}{-1 has a profound effect and found that normalization with respect to T results in ...
... compute — log P({O1(t)}=1, Q(T.) = qx (H1) | ?ti) where Q(T.) = q.v.(?(1), i.e., QN is obtained from hti. We observed that the length of sequence {O(t)}{-1 has a profound effect and found that normalization with respect to T results in ...
30. lappuse
... compute features based on distances and angles among points. Windows of adjacent points are assembled around centers consisting primarily of local extrema in z and y; point feature vectors are spliced together to form window feature ...
... compute features based on distances and angles among points. Windows of adjacent points are assembled around centers consisting primarily of local extrema in z and y; point feature vectors are spliced together to form window feature ...
53. lappuse
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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