Results 71 to 80 of about 352 (167)

Enhancing Arabic handwritten word recognition: a CNN-BiLSTM-CTC architecture with attention mechanism and adaptive augmentation

Discover Applied Sciences
Optical character recognition (OCR) for Arabic presents unique challenges due to the script's cursive nature, contextual letter forms, multiple ligatures, the presence of diacritics, and the high variability in handwritten styles. This work introduces an
Bounour Imane, Ammour Alae, Khaissidi Ghizlane, Mostafa Mrabti   +3 more
doaj   +1 more source

An Efficient Feature-Driven Approach for Intra-Connection Identification in Offline Arabic Handwritten Text Segmentation [PDF]

Egyptian Journal of Pure and Applied Science
Offline Arabic handwriting text segmentation (OAHTS), which splits handwritten Arabic text into lines, words, and individual characters, is an essential step in optical character recognition (OCR) and document analysis.
Nader Hussien, Wael Zakaria, Fayed Ghaleb, Mohammad Abdel-Rahman   +3 more
doaj   +1 more source

Handwritten Amharic Word Recognition With Additive Attention Mechanism

IEEE Access
Amharic stands as the second most widely spoken Semitic language globally, trailing only Arabic. As a result, it is a highly resourceful language for hardcopy-document collection, and automatic recognition technology is required.
Ruchika Malhotra, Maru Tesfaye Addis
doaj   +1 more source

Invizo: Arabic Handwritten Document Optical Character Recognition Solution

CoRR
Converting images of Arabic text into plain text is a widely researched topic in academia and industry. However, recognition of Arabic handwritten and printed text presents difficult challenges due to the complex nature of variations of the Arabic script.
Alhossien Waly, Bassant Tarek, Ali Feteha, Rewan Yehia, Gasser Amr, Walid Gomaa 0001, Ahmed Fares   +6 more
openaire   +2 more sources

ADVANCED STROKE LABELING TECHNIQUE BASED ON DIRECTIONS FEATURES FOR ARABIC CHARACTER SEGMENTATION

Asia-Pacific Journal of Information Technology and Multimedia, 2019
Offline Character segmentation of text images is an important step in many document image analysis and recognition (DIAR) applications. However, the character segmentation of both writing styles (printed and handwritten) remains an open problem. Moreover,
Tarik Abdel-Kareem Abu-Ain, Siti Norul Huda Sheikh Abdullah, Khairuddin Omar, Siti Zaharah Abd Rahman   +3 more
doaj   +1 more source

A Hybrid Model for Arabic Script Recognition Based on CNN-CBAM and BLSTM

Jordanian Journal of Computers and Information Technology
Handwriting recognition, particularly for Arabic, is a very challenging field of research due to various complex factors such as the presence of ligatures, cursive writing style, slant variations, diacritics, overlapping, and other difficult problems ...
MOHAMED DAHBALI, Noureddine Aboutabit, Nidal Lamghari   +2 more
doaj   +1 more source

Dhad—A Children’s Handwritten Arabic Characters Dataset for Automated Recognition

Applied Sciences
This study delves into the intricate realm of recognizing handwritten Arabic characters, specifically targeting children’s script. Given the inherent complexities of the Arabic script, encompassing semi-cursive styles, distinct character forms based on ...
Sarab AlMuhaideb, Najwa Altwaijry, Ahad D. AlGhamdy, Daad AlKhulaiwi, Raghad AlHassan, Haya AlOmran, Aliyah M. AlSalem   +6 more
doaj   +1 more source

A Genetic-LVQ neural networks approach for handwritten Arabic character recognition

Artificial Intelligence Research, 2018
Handwritten recognition systems are a dynamic field of research in areas of artificial intelligence. Many smart devices available in the market such as pen-based computers, tablets, mobiles with handwritten recognition technology need to rely on efficient handwritten recognition systems.
openaire   +2 more sources

Designing a Novel CNN–LSTM-based Model for Arabic Handwritten Character Recognition for the Visually Impaired Person

Journal of Disability Research
The field of healthcare has undergone a radical change as a consequence of the latest advancements in deep learning. Recently, the development of visual substitutes for visually impaired people (VIP) has significantly aided research on assistive ...
Manel Ayadi, Nesrine Masmoudi, Latifa Almuqren, Hadeel Saeed Alshahrani, Raneem Oudah Aljohani   +4 more
doaj   +1 more source

A deep learning based approach for extracting Arabic handwriting: applied calligraphy and old cursive. [PDF]

PeerJ Comput Sci, 2023
Zerdoumi S, Jhanjhi NZ, Ariyaluran Habeeb RA, Hashem IAT.   +3 more
europepmc   +1 more source