Results 21 to 30 of about 427 (175)
End-To-End Deep-Learning-Based Tamil Handwritten Document Recognition and Classification Model
IEEE Access, 2023 Overview: Handwriting recognition (HR) involves converting handwritten text into machine-readable text. Tamil handwritten document recognition remains a challenging process in various text real-world applications owing to the differences in the sizes ...
C. Vinotheni, S. Lakshmana Pandian
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PHTI: Pashto Handwritten Text Imagebase for Deep Learning Applications
IEEE Access, 2022 Document Image Analysis (DIA) is one of the research areas of Artificial Intelligence (AI) that converts document images into machine-readable codes. In DIA systems, Optical Character Recognition (OCR) plays a key role in digitizing document images.
Ibrar Hussain +5 more
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End-to-End Historical Handwritten Ethiopic Text Recognition Using Deep Learning
IEEE Access, 2023 Recognizing handwritten text is a challenging task, especially for scripts with numerous alphabets and symbols. The Ethiopic script has a vast character set and is used for historical documents in typewritten, handwritten, and hand-printed forms. However,
Ruchika Malhotra, Maru Tesfaye Addis
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Handwritten Character Recognition to Obtain Editable Text [PDF]
E3S Web of Conferences, 2023 Optical character recognition involves distinguishing, grouping, and, in specific cases, remedying optical images/designs in a computerized picture.
Pravalika Jella +3 more
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International Journal of Advanced Research in Science, Communication and TechnologyHandwritten text detection refers to the capacity of a computer system to interpret and understand handwritten input from various sources such as paper documents, touch displays, and photographs. Within the realm of pattern recognition, one specific area is handwritten text recognition, which involves categorizing and interpreting handwritten text.
null Tanishq Rampure +4 more
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IEEE Access, 2021 Offline handwritten Chinese text recognition is one of the most challenging tasks in that it involves various writing styles, complex character-touching, and large number of character categories.
Yintong Wang +3 more
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Handwritten Text Recognition for Documentary Medieval Manuscripts [PDF]
Journal of Data Mining and Digital Humanities, 2023 Handwritten Text Recognition (HTR) techniques aim to accurately recognize sequences of characters in input manuscript images by training artificial intelligence models to capture historical writing features.
Sergio Torres Aguilar, Vincent Jolivet
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A Scalable Handwritten Text Recognition System [PDF]
2019 International Conference on Document Analysis and Recognition (ICDAR), 2019 Many studies on (Offline) Handwritten Text Recognition (HTR) systems have focused on building state-of-the-art models for line recognition on small corpora. However, adding HTR capability to a large scale multilingual OCR system poses new challenges.
R. Reeve Ingle +4 more
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The Challenges of Recognizing Offline Handwritten Chinese: A Technical Review
Applied Sciences, 2023 Offline handwritten Chinese recognition is an important research area of pattern recognition, including offline handwritten Chinese character recognition (offline HCCR) and offline handwritten Chinese text recognition (offline HCTR), which are closely ...
Lu Shen +5 more
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Proceedings of the 2013 ACM symposium on Document engineering, 2013 The tranScriptorium project aims to develop innovative, efficient and cost-effective solutions for annotating handwritten historical documents using modern, holistic Handwritten Text Recognition (HTR) technology. Three actions are planned in tranScriptorium: i) improve basic image preprocessing and holistic HTR techniques; ii) develop novel indexing ...
Joan-Andreu Sánchez +7 more
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