A scarce dataset for ancient Arabic handwritten text recognition
Data in BriefDeveloping Deep Learning Optical Character Recognition is an active area of research, where models based on deep neural networks are trained on data to eventually extract text within an image. Even though many advances are currently being made in this area in general, the Arabic OCR domain notably lacks a dataset for ancient manuscripts.
Rayyan Najam, Safiullah Faizullah
openaire +4 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
Application of soft computing techniques in machine reading of Quranic Kufic manuscripts
Journal of King Saud University: Computer and Information Sciences, 2022 Research work in the field of offline Arabic handwriting recognition has seen an exponential growth during past decades. Despite much work dedicated to the recognition of handwritten Arabic text, there remains a lot to achieve in this regard.
Aasim Zafar, Arshad Iqbal
doaj +1 more source
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 Handwritten Text Recognition Systems and Challenges and Opportunities [PDF]
The Egyptian Journal of Language Engineering, 2023 Arabic handwritten text recognition faces significant challenges despite the large number of Arabic speakers. A critical review paper has analyzed previous research in this field, identifying problem areas and challenges faced by researchers.
Esraa El-Awadly +2 more
doaj +1 more source
Attention based unified architecture for Arabic text detection on traffic panels to advance autonomous navigation in natural scenes. [PDF]
Sci RepThe increasing reliance on autonomous navigation systems necessitates robust methods for detecting and recognizing textual information in natural scenes, especially in complex scripts like Arabic.
Hassan BM, Gamel SA, Talaat FM.
europepmc +2 more sources
Arabic Sign Language Recognition System: Using an Image-Based hand Gesture Detection Method to help Deaf and Dump Children to Engage in Education [PDF]
Mağallaẗ Kulliyyaẗ Al-Adāb Bi-Qinā, 2023 Hand gestures help individuals communicate in daily life. Sign languages, however, employ hand motions extensively. People with hearing impairments use sign language.
Amr Mohmed Soliman +2 more
doaj +1 more source
Attention-Based CNN-RNN Arabic Text Recognition from Natural Scene Images
Forecasting, 2021 According to statistics, there are 422 million speakers of the Arabic language. Islam is the second-largest religion in the world, and its followers constitute approximately 25% of the world’s population.
Hanan Butt +4 more
doaj +1 more source
Intelligent handwritten recognition using hybrid CNN architectures based-SVM classifier with dropout
Journal of King Saud University: Computer and Information Sciences, 2022 Text recognition in Arabic handwritten scripts is an active research field. These recognition systems face numerous challenges, including enormous open data-bases, infinite variation in people’s handwriting, and freestyle.
Amani Ali Ahmed Ali, Suresha Mallaiah
doaj +1 more source