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Handwritten Text Recognition Using Machine Learning
2023 International Conference on Sustainable Emerging Innovations in Engineering and Technology (ICSEIET), 2023Handwritten text recognition is a difficult task with numerous applications in document analysis, postal automation, and historical document preservation.
K. Saini +4 more
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AttentionHTR: Handwritten Text Recognition Based on Attention Encoder-Decoder Networks
International Workshop on Document Analysis Systems, 2022. This work proposes an attention-based sequence-to-sequence model for handwritten word recognition and explores transfer learning for data-efficient training of HTR systems.
D. Kass, Ekta Vats
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Recognition of Short Handwritten Texts
2004Building on our 10-year-experience with script recognition systems, a new reader generation was designed. Previously, only single handwritten words were compared against a dictionary. Now a short text is modeled and processed as a whole. The system does not proceed in a linear fashion anymore, but uses feedback between image processing, character ...
Michael Boldt, Christopher Asp
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Handwritten Text Recognition using Deep Learning Algorithms
International Joint Conference on the Analysis of Images, Social Networks and Texts, 2022Since a pen is more convenient than a keyboard, most scripts are now produced by hand; this often leads to mistakes due to the illegibility of human handwriting. To combat this issue, handwriting recognition has rapidly emerged as a top research priority.
Arbaj Ansari +4 more
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An architecture for handwritten text recognition systems
International Journal on Document Analysis and Recognition, 1999This paper presents an end-to-end system for reading handwritten page images. Five functional modules included in the system are introduced in this paper: (i) pre-processing, which concerns introducing an image representation for easy manipulation of large page images and image handling procedures using the image representation; (ii) line separation ...
Gyeonghwan Kim +2 more
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Benchmarking Large Language Models for Handwritten Text Recognition
J. DocumentationThe aim of this work is to provide an overview of the current capabilities of Multimodal Large Language Models (MLLMs) for Handwritten Text Recognition (HTR), assessing their potential when compared to traditional task-specific, supervised models.
Giorgia Crosilla +2 more
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Handwritten Text Recognition Using CRNN
2022 8th International Conference on Contemporary Information Technology and Mathematics (ICCITM), 2022Text recognition is one of the significant and demanding jobs that needed to keep diving into finding the stability result because of the wide range of real-world applications' use.
A. A. Idris, Dujan B. Taha
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PLATTER: A Page-Level Handwritten Text Recognition System for Indic Scripts
arXiv.orgIn recent years, the field of Handwritten Text Recognition (HTR) has seen the emergence of various new models, each claiming to perform competitively better than the other in specific scenarios.
Badri Vishal Kasuba +4 more
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Influence of text line segmentation in Handwritten Text Recognition
2015 13th International Conference on Document Analysis and Recognition (ICDAR), 2015Text line segmentation is the process by which text lines in a document image are localized and extracted. It is an important step in off-line Handwritten Text Recognition (HTR) given that the input of these systems is the line image of the text to be transcribed.
Verónica Romero 0001 +4 more
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Handwritten Khmer text recognition
2016 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE), 2016This paper proposes a model for an offline handwritten Khmer character recognition. We make use of two dimensional Fourier transformation for feature selection and feed-forward Artificial Neural Net as classification tool. The recognition system allows using the nature of Khmer writing, which is an example of alphasyllabary (Abugida) writing systems ...
Bayram Annanurov, Norliza Mohd Noor
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