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Handwritten text generation and strikethrough characters augmentation
Компьютерная оптика, 2022 We introduce two data augmentation techniques, which, used with a Resnet-BiLSTM-CTC network, significantly reduce Word Error Rate and Character Error Rate beyond best-reported results on handwriting text recognition tasks.
A.V. Shonenkov +5 more
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Handwritten Text Recognition for Bengali [PDF]
2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR), 2016 This work has been partially supported through the European Union’s H2020 grant READ (Recognition and Enrichment of Archival Documents) (Ref: 674943) and partially supported by MINECO/FEDER, UE under project TIN2015-70924-C2-1-R.
Sanchez, Joan Andreu, Pal, Umapada
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HANA: A handwritten name database for offline handwritten text recognition
Explorations in Economic History, 2022 Methods for linking individuals across historical data sets, typically in combination with AI based transcription models, are developing rapidly. Probably the single most important identifier for linking is personal names. However, personal names are prone to enumeration and transcription errors and although modern linking methods are designed to ...
Christian M. Dahl +3 more
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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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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 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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Watch Your Strokes: Improving Handwritten Text Recognition with Deformable Convolutions [PDF]
, 2021 Handwritten Text Recognition (HTR) in free-layout pages is a valuable yet challenging task which aims to automatically understand handwritten texts. State-of-the-art approaches in this field usually encode input images with Convolutional Neural Networks,
Rita Cucchiara +4 more
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