Results 1 to 10 of about 145 (124)

Advancements and Challenges in Handwritten Text Recognition: A Comprehensive Survey [PDF]

Journal of Imaging
Handwritten Text Recognition (HTR) is essential for digitizing historical documents in different kinds of archives. In this study, we introduce a hybrid form archive written in French: the Belfort civil registers of births.
Wissam AlKendi, Franck Gechter, Laurent Heyberger, Christophe Guyeux   +3 more
doaj   +4 more sources

HTR for Greek Historical Handwritten Documents [PDF]

Journal of Imaging, 2021
Offline handwritten text recognition (HTR) for historical documents aims for effective transcription by addressing challenges that originate from the low quality of manuscripts under study as well as from several particularities which are related to the ...
Lazaros Tsochatzidis, Symeon Symeonidis, Alexandros Papazoglou, Ioannis Pratikakis   +3 more
doaj   +2 more sources

Integrated interdisciplinary workflows for research on historical newspapers: Perspectives from humanities scholars, computer scientists, and librarians. [PDF]

J Assoc Inf Sci Technol, 2022
Abstract This article considers the interdisciplinary opportunities and challenges of working with digital cultural heritage, such as digitized historical newspapers, and proposes an integrated digital hermeneutics workflow to combine purely disciplinary research approaches from computer science, humanities, and library work.
Oberbichler S, Boroş E, Doucet A, Marjanen J, Pfanzelter E, Rautiainen J, Toivonen H, Tolonen M.   +7 more
europepmc   +2 more sources

Enhancement of handwritten text recognition using AI-based hybrid approach [PDF]

MethodsX
Handwritten 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, Shruti Patil, Ketan Kotecha   +2 more
doaj   +2 more sources

Enhancing handwritten text recognition accuracy with gated mechanisms [PDF]

Scientific Reports
Handwritten 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, C. Dhanamjayulu, Tai-hoon Kim, Suhaib Ahmed, Si-Yeong Kim, A. S. Kumar, Visalakshi Annepu, Shafiq Ahmad   +7 more
doaj   +2 more sources

Ensemble automated approaches for producing high-quality herbarium digital records. [PDF]

Appl Plant Sci
Abstract Premise One of the slowest steps in digitizing natural history collections is converting labels associated with specimens into a digital data record usable for collections management and research. Here, we address how herbarium specimen labels can be converted into digital data records via extraction into standardized Darwin Core fields ...
Guralnick RP, LaFrance R, Allen JM, Denslow MW.   +3 more
europepmc   +2 more sources

HTR-VT: Handwritten text recognition with vision transformer

Pattern Recognition
Accepted to Pattern ...
Tinglong Tang, Xi Shen
exaly   +4 more sources

Historical Text Line Segmentation Using Deep Learning Algorithms: Mask-RCNN against U-Net Networks [PDF]

Journal of Imaging
Text line segmentation is a necessary preliminary step before most text transcription algorithms are applied. The leading deep learning networks used in this context (ARU-Net, dhSegment, and Doc-UFCN) are based on the U-Net architecture.
Florian Côme Fizaine, Patrick Bard, Michel Paindavoine, Cécile Robin, Edouard Bouyé, Raphaël Lefèvre, Annie Vinter   +6 more
doaj   +2 more sources

BN-HTRd: A Benchmark Dataset for Document Level Offline Bangla Handwritten Text Recognition (HTR) and Line Segmentation

, 2023
We introduce a new dataset for offline Handwritten Text Recognition (HTR) from images of Bangla scripts comprising words, lines, and document-level annotations. The BN-HTRd dataset is based on the BBC Bangla News corpus, meant to act as ground truth texts.
Md Ataur Rahman
exaly   +3 more sources

Self-HTR: A Novel Self-supervised Handwritten Text Recognition Framework Using Generative Adversarial Networks

Lecture Notes in Computer Science
Robust handwritten text recognition (HTR) systems require diverse and abundant annotated data, which can be expensive to acquire. Unlike commonly used methods, such as transfer learning and data augmentation, that reduce the need for labeled data, this article proposes a novel self-supervised handwritten text recognition (HTR) framework to eliminate ...
Lisa Koopmans, Maruf A Dhali, Lambert Schomaker   +2 more
exaly   +3 more sources