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Text extraction using OCR: a systematic review
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 …
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A comprehensive study of imagenet pre-training for historical document image analysis
Automatic analysis of scanned historical documents comprises a wide range of image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 …
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
(57) ABSTRACT A computer implemented method for adaptive optical char acter recognition
on a document with distorted characters includes performing a distortion-correction …
on a document with distorted characters includes performing a distortion-correction …
[PDF][PDF] Unsupervised transcription of historical documents
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 …
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
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 …
approach for data capture is necessary. Cognitive automation (CA), that is, automation of …
Optical character recognition and neural machine translation using deep learning techniques
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 …
various fields. Many researchers have used several deep learning algorithms for text …
Word spotting in historical printed documents using shape and sequence comparisons
Information spotting in scanned historical document images is a very challenging task.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 …
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.
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 …
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
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 …
recognition of printed documents. The same is true for Bangla, a major Indian script. All …
Character recognition in historical handwritten documents–a survey
Digitization and Recognition of handwritten documents have become popular with the
growth of advances in Computing. Even after the introduction of new technologies …
growth of advances in Computing. Even after the introduction of new technologies …