2014
DOI: 10.1016/j.patcog.2013.08.014
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Learning-based word spotting system for Arabic handwritten documents

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Cited by 45 publications
(28 citation statements)
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“…Both Islamic boarding school and Islamic school, actually, agree on that Arabic language is a unity, but techniques of learn may be different. The important one is that they should be done in balance and consistently (Kern, Lingnau, & Paul, 2015;Khayyat, Lam, & Suen, 2014).…”
Section: Nazhariyah Al-wihdah: An Approach In Arabic Learnmentioning
confidence: 99%
“…Both Islamic boarding school and Islamic school, actually, agree on that Arabic language is a unity, but techniques of learn may be different. The important one is that they should be done in balance and consistently (Kern, Lingnau, & Paul, 2015;Khayyat, Lam, & Suen, 2014).…”
Section: Nazhariyah Al-wihdah: An Approach In Arabic Learnmentioning
confidence: 99%
“…The authors in [30] proposed a model-based similarity between vector sequences of handwritten word images with semi-continuous Gaussian mixture HMMs. Coherent learning segmentation based Arabic handwritten word spotting system [31] in which can adapt to the nature of Arabic handwriting and the system recognizes Pieces of Arabic Words (PAWs). Based on inkball character models, Howe [28] proposed a word spotting method using synthetic models composed of individual characters.…”
Section: Related Workmentioning
confidence: 99%
“…The proposed words spotting system achieved recall rates 95.75% on average while keeping the precision at 96.47% on average. M. Khayyat et al [5] develop a learning-based word spotting system for Arabic handwritten documents by adapting the nature of Arabic handwriting, which can have variable boundaries between words and sub words. This technique has performance a recall of 96.0% for recall and 95.4 for precision.…”
Section: Abdulmunim and Abassmentioning
confidence: 99%