Results 11 to 20 of about 2,638,937 (286)
Integrating CNN and transformer architectures for superior Arabic printed and handwriting characters classification [PDF]
Scientific ReportsOptical Character Recognition (OCR) systems play a crucial role in converting printed Arabic text into digital formats, enabling various applications such as education and digital archiving.
Mohammed R. Al-Maamari +3 more
doaj +2 more sources
Arabic speech recognition model using Baidu's deep and cluster learning [PDF]
Frontiers in Artificial IntelligenceThis study involves extracting the spectrum from the Arabic raw, unlabeled audio signal and producing Mel-frequency cepstral coefficients (MFCCs). The clustering algorithm groups the retrieved MFCCs with analogous features.
Fawaz S. Al-Anzi +1 more
doaj +2 more sources
Offline printed Arabic character recognition [PDF]
, 2012 Optical Character Recognition (OCR) shows great potential for rapid data entry, but has limited success when applied to the Arabic language. Normal OCR problems are compounded by the right-to-left nature of Arabic and because the script is largely connected.
AbdelRaouf, Ashraf M +1 more
openaire +4 more sources
A Database for Arabic Handwritten Character Recognition [PDF]
Procedia Computer Science, 2015 AbstractThis paper proposes an image database for Arabic handwritten character recognition (AHCR). In this paper, the Arabic handwritten images character database written by multi writers is proposed. This database is eligible for Arabic handwritten recognition research.
AlKhateeb, Jawad H.
openaire +2 more sources
Performance of hidden Markov model and dynamic Bayesian network classifiers on handwritten Arabic word recognition [PDF]
, 2011 This paper presents a comparative study of two machine learning techniques for recognizing handwritten Arabic words, where hidden Markov models (HMMs) and dynamic Bayesian networks (DBNs) were evaluated.
Jinchang Ren +11 more
core +4 more sources
Component-based Segmentation of words from handwritten Arabic text [PDF]
, 2009 Efficient preprocessing is very essential for automatic recognition of handwritten documents. In this paper, techniques on segmenting words in handwritten Arabic text are presented.
AlKhateeb, J. H. +3 more
core +5 more sources
Experimental evaluation of Arabic OCR systems [PDF]
International Journal of Crowd Science, 2017 Purpose – The aim of this paper is to experimentally evaluate the effectiveness of the state-of-the-art printed Arabic text recognition systems to determine open areas for future improvements.
Mansoor Alghamdi, William Teahan
doaj +1 more source
Arabic Character Recognition [PDF]
, 2014 Although optical character recognition of printed texts has been a focus of research for the last few decades, Arabic printed text, being cursive, still poses a challenge. The challenge is twofold: segmenting words into letters and identifying individual letters. We describe a method that combines the two tasks, using multiple grids of SIFT descriptors
Nachum Dershowitz, Andrey Rosenberg
openaire +2 more sources
IEEE Access, 2023 Owing to the linguistic richness of the Arabic language, which contains more than 6000 roots, building a reliable Arabic language model for Arabic speech recognition systems faces many challenges.
Mona A. Azim +2 more
doaj +1 more source
Comprehensive collection for Arabic characters and numbers written by hand [PDF]
Engineering and Technology Journal, 2017 An Optical Character Recognition system for Arabic language should recognize Arabic handwritten words. However, it is difficult to find a freely accessible and comprehensive database of all Arabic words that can be employed for this purpose.
S.A. Ahmed
doaj +1 more source