Automated Handwritten Text Recognition [PDF]
E3S Web of Conferences, 2023 A computer’s capacity to recognize and convert handwritten inputs from sources like photographs and paper documents into digital format is known as Automated Handwritten Text Recognition (AHTR).
Ram Kumar R.P. +4 more
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Enhancement of handwritten text recognition using AI-based hybrid approach [PDF]
MethodsXHandwritten text recognition (HTR) within computer vision and image processing stands as a prominent and challenging research domain, holding significant implications for diverse applications.
Supriya Mahadevkar +2 more
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ET-Network: A novel efficient transformer deep learning model for automated Urdu handwritten text recognition. [PDF]
PLoS ONEAutomatic Urdu handwritten text recognition is a challenging task in the OCR industry. Unlike printed text, Urdu handwriting lacks a uniform font and structure. This lack of uniformity causes data inconsistencies and recognition issues. Different writing
Ameer Hamza, Shengbing Ren, Usman Saeed
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Multi-stage deep learning framework for robust recognition of overlapping and faded handwritten text in bank cheques [PDF]
Scientific ReportsAutomated recognition of handwritten text on bank cheques is crucial for streamlining financial transactions and reducing manual errors. However, traditional systems often encounter two significant challenges: differentiating overlapping handwritten and ...
Hitesh Chaitanyaswami +6 more
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Handwritten Text Recognition and Linguistic Research
Digital Humanities in the Nordic and Baltic Countries Publications, 2020 This paper presents ongoing work with automatic transcription of handwritten, phonetically precise dialect texts from the south-west of Sweden (collected in the 1890s).
Erik Magnusson Petzell
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Enhancing handwritten text recognition accuracy with gated mechanisms [PDF]
Scientific ReportsHandwritten Text Recognition (HTR) is a challenging task due to the complex structures and variations present in handwritten text. In recent years, the application of gated mechanisms, such as Long Short-Term Memory (LSTM) networks, has brought ...
Ravikumar Chinthaginjala +7 more
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Online Chinese and English Handwriting Recognition Method Based on Multiple Rules and Path Evaluation [PDF]
Jisuanji gongcheng, 2022 Handwritten text recognition is mainly used in text input technology, which plays a key role in the development of human-computer interaction.To address the lack of functionality for Chinese and English mixed handwritten text recognition in most online ...
FU Pengbin, LIU Penghui, YANG Huirong, DONG Aojing
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HANA: A handwritten name database for offline handwritten text recognition [PDF]
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 ...
Dahl, Christian M. +3 more
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CNN-RNN BASED HANDWRITTEN TEXT RECOGNITION
ICTACT Journal on Soft Computing, 2021 At present most of the scripts are handwritten due to the ease of using a pen tip in place of a keyboard, hence errors are common due to illegibility of the human handwriting. To avoid this problem handwriting recognition is essential.
Hemanth G R +4 more
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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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