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Titlebook: Document Analysis Systems V; 5th International Wo Daniel Lopresti,Jianying Hu,Ramanujan Kashi Conference proceedings 2002 Springer-Verlag G

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21#
發(fā)表于 2025-3-25 04:29:24 | 只看該作者
22#
發(fā)表于 2025-3-25 07:44:26 | 只看該作者
23#
發(fā)表于 2025-3-25 12:42:43 | 只看該作者
Using Stroke-Number-Characteristics for Improving Efficiency of Combined Online and Offline Japaneseency based on a stroke number is different for a common on-line and offline recognizer. Later, we demonstrate on elementary combination rules, such as sum-rule and max-rule that using this information increases a recognition rate.
24#
發(fā)表于 2025-3-25 16:22:41 | 只看該作者
25#
發(fā)表于 2025-3-25 20:32:57 | 只看該作者
Transition in the Baltic Statesnges in the probability that the characters are from different populations when the model parameters vary correlate with the relationship between observable degradation features and the model parameters. The paper also shows which features have the largest impact on the image.
26#
發(fā)表于 2025-3-26 02:59:54 | 只看該作者
https://doi.org/10.1007/978-1-4419-6238-6in India, especially in the post and telegraph department where OCR can assist the staff in sorting mail. Character recognition can also form a part in applications like intelligent scanning machines, text to speech converters, and automatic language-to-language translators.
27#
發(fā)表于 2025-3-26 04:42:30 | 只看該作者
Miguel á. Tinoco,Francisco Venegas Martínezorrelation method based on a global approach. The two algorithms are combined by a voting strategy. Experimental results showed that the combination of the two algorithms improves significantly the verification performance both on “false-acceptance error rate” and “false-rejection error rate”.
28#
發(fā)表于 2025-3-26 09:20:06 | 只看該作者
Transition, Turbulence and Combustion much higher number of samples per category. In this paper, we experiment with off-line classifiers trained with up to 1550 patterns for 3036 categories respectively. We show that this bigger training set size indeed leads to improved recognition rates compared to the smaller training sets normally used.
29#
發(fā)表于 2025-3-26 15:29:58 | 只看該作者
30#
發(fā)表于 2025-3-26 20:43:29 | 只看該作者
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