Text extraction using OCR: a systematic review

R Mittal, A Garg - 2020 second international conference on …, 2020‏ - ieeexplore.ieee.org
In the digital era, almost everything is automated, and information is stored and
communicated in digital forms. However, there are several situations where the data is not …

A comprehensive study of imagenet pre-training for historical document image analysis

L Studer, M Alberti, V Pondenkandath… - 2019 International …, 2019‏ - ieeexplore.ieee.org
Automatic analysis of scanned historical documents comprises a wide range of image
analysis tasks, which are often challenging for machine learning due to a lack of human …

Adaptive optical character recognition on a document with distorted characters

DS Chevion, V Kluzner, A Tzadok, E Walach - US Patent 8,494,273, 2013‏ - Google Patents
(57) ABSTRACT A computer implemented method for adaptive optical char acter recognition
on a document with distorted characters includes performing a distortion-correction …

[PDF][PDF] Unsupervised transcription of historical documents

T Berg-Kirkpatrick, G Durrett… - Proceedings of the 51st …, 2013‏ - aclanthology.org
We present a generative probabilistic model, inspired by historical printing processes, for
transcribing images of documents from the printing press era. By jointly modeling the text of …

Application of cognitive automation to structuring data, driving existing business models, and creating value between legacy industries

C Helm, TA Herberger, N Gerold - International Journal of Innovation …, 2022‏ - World Scientific
To build high quality datasets and unlock the value of unstructured data, a systematic
approach for data capture is necessary. Cognitive automation (CA), that is, automation of …

Optical character recognition and neural machine translation using deep learning techniques

KC Shekar, MA Cross, V Vasudevan - Innovations in Computer Science …, 2021‏ - Springer
Over the years, the applications of text detection and text translation have expanded across
various fields. Many researchers have used several deep learning algorithms for text …

Word spotting in historical printed documents using shape and sequence comparisons

K Khurshid, C Faure, N Vincent - Pattern Recognition, 2012‏ - Elsevier
Information spotting in scanned historical document images is a very challenging task. The
joint use of the mechanical press and of human controlled inking introduced great variability …

[PDF][PDF] Transforming Hand Drawn Wireframes into Front-End Code with Deep Learning.

S Riaz, A Arshad, SS Band… - Computers, Materials & …, 2022‏ - researchgate.net
The way towards generating a website front end involves a designer settling on an idea for
what kind of layout they want the website to have, then proceeding to plan and implement …

A hybrid deep architecture for robust recognition of text lines of degraded printed documents

C Biswas, PS Mukherjee, K Ghosh… - 2018 24th …, 2018‏ - ieeexplore.ieee.org
During the last 20 years, significant research studies have been undertaken for automatic
recognition of printed documents. The same is true for Bangla, a major Indian script. All …

Character recognition in historical handwritten documents–a survey

N Babu, A Soumya - 2019 international conference on …, 2019‏ - ieeexplore.ieee.org
Digitization and Recognition of handwritten documents have become popular with the
growth of advances in Computing. Even after the introduction of new technologies …