A Multi-Agent Approach to Arabic Handwritten Text Segmentation

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Journal of Intelligent Learning Systems and Applications

ISSN Print: 2150-8402
ISSN Online: 2150-8410
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"A Multi-Agent Approach to Arabic Handwritten Text Segmentation"
written by Ashraf Elnagar, Rahima Bentrcia,
published by Journal of Intelligent Learning Systems and Applications, Vol.4 No.3, 2012

has been cited by the following article(s):

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CrossRef

[1]	Professor's scientific research: Rahima Bentrcia
	2022

[2]	The scientific work of: BENTRCIA Rahima
	2022

[3]	SCIENCES FACULTY SCIENTIFIC WORKS
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[4]	TRAVAUX SCIENTIFIQUES DE LA FACULTE de mathématiques et de l'informatique
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[5]	Advanced Stroke Labeling Technique Based on Directions Features for Arabic Character Segmentation
	2019

[6]	ADVANCED STROKE LABELLING TECHNIQUE BASED ON DIRECTIONS FEATURES FOR ARABIC CHARACTER SEGMENTATION
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[7]	Classification of Arabic Writing Styles in Ancient Arabic Manuscripts
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[8]	PERBANDINGAN HASIL SEGMENTASI KATA TULISAN TANGAN ARAB MENGGUNAKAN EKSTRAKSI FITUR ZONING DAN WUMI
	2018

[9]	Arabic character extraction and recognition using traversing approach.
	2018

[10]	Efficient segmentation of arabic handwritten characters using structural features.
	2017

[11]	A Novel Method to Detect Segmentation points of Arabic Words using Peaks and Neural Network
	2017

[12]	Kombinasi Metode Interest Point Dalam Proses Segmentasi Dan City_Block Dalam Proses Pengenalan Huruf Hijaiyyah Pada Tulisan Cetak Arab …
	2017

[13]	Graph Modeling based Segmentation of Handwritten Arabic Text into Constituent Subwords.
	2016

[14]	Text lines Segmentation of Handwritten Arabic Script using Outer Isothetic Cover
	The International Congress for global Science and Technology, 2016

[15]	Graph Modeling based Segmentation of Handwritten Arabic Text into Constituent Sub-words
	2016

[16]	Efficient Segmentation of Arabic Handwritten Characters Using Structural Features
	2015

[17]	Arabic Character Extraction and Recognition using Traversing Approach
	2015

[18]	Dataset size and dimensionality reduction approaches for handwritten farsi digits and characters recognition
	2015

[19]	An Enhanced Technique for Offline Arabic Handwritten Words Segmentation
	Computational Linguistics and Intelligent Text Processing, 2015

[20]	and Intelligent Text Processing
	CICLing: International Conference on Intelligent Text Processing and Computational Linguistics, 2015

[21]	A Recognition-Based Approach to Segmenting Arabic Handwritten Text
	Journal of Intelligent Learning Systems and Applications, 2015

[22]	Improved Arabic Handwriting Word Segmentation Approach using Random Forests
	2015

[23]	An Enhanced Technique for Offline Arabic Handwritten Words Segmentation.
	2015

[1]	A Recognition-Based Approach to Segmenting Arabic Handwritten Text Journal of Intelligent Learning Systems and Applications, 2015 DOI:10.4236/jilsa.2015.74009

[2]	Improved Arabic handwriting word segmentation approach using Random Forests 2015 IEEE/ACS 12th International Conference of Computer Systems and Applications (AICCSA), 2015 DOI:10.1109/AICCSA.2015.7507105

[3]	Computational Linguistics and Intelligent Text Processing Lecture Notes in Computer Science, 2015 DOI:10.1007/978-3-319-18117-2_50

[4]	Computational Linguistics and Intelligent Text Processing Lecture Notes in Computer Science, 2015 DOI:10.1007/978-3-319-18117-2_50

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	customer@scirp.org
	+86 18163351462(WhatsApp)
	1655362766

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