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ABBYY USA Software House Inc optical character recognition (ocr) analysis
Optical Character Recognition (Ocr) Analysis, supplied by ABBYY USA Software House Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/optical+character+recognition+(ocr/optical+character+recognition+software/pmc11893318-40-7-13
Average 90 stars, based on 1 article reviews
optical character recognition (ocr) analysis - by Bioz Stars, 2026-09
90/100 stars

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Article Title: Annual and state-level data on U.S. total fertility rates, 1931–present
Article Snippet: Fig 1 Data transcription was performed using Optical Character Recognition (OCR) analysis through ABBYY software, transcribing the number of births for each state-year, categorized by maternal age and stratified by race.

Article Title: Unpacking Unstructured Data: A Pilot Study on Extracting Insights from Neuropathological Reports of Parkinson’s Disease Patients using Large Language Models
Article Snippet: Neuropathological reports in pdf file format were converted to HTML using the ABBYY FineReader Optical Character Recognition (OCR) tool ( https://pdf.abbyy.com/ ).

Article Title: Social networks from dailies: the observer’s point of view
Article Snippet: Each text was digitized using Czur ET24 Pro scanner, which includes a powerful OCR (optical character recognition) software developed by the company ABBYY.

Article Title: Unpacking unstructured data: A pilot study on extracting insights from neuropathological reports of Parkinson’s Disease patients using large language models
Article Snippet: Neuropathological reports in PDF file format were converted to HTML using the ABBYY FineReader Optical Character Recognition (OCR) tool ( https://pdf.abbyy.com/ ).

Article Title: Developing Strategies to Improve Textbook Design Using Synergy of Native and Learner Corpora.
Article Snippet: The research aims to enhance the handling of modal verbs (MVs) in EFL textbooks by leveraging perspectives from corpora that include both native speakers’ language data and the language data of individuals who are learning the language.. To assess the authenticity of language in textbooks, an analysis between the native corpus and a collection of language data compiled from textbook is conducted.. The research delves into the developmental patterns of MV usage among learners through a stratified analysis of student essays (Grades 7, 8, 9).

Article Title: Methods and systems for artificial intelligence-assisted document annotation
Article Snippet: As illustrated in FIG. 1, the document information extraction platform residing within the AI service platform may comprise a variety of document processing tools, e.g., the ABBYY® FineReader Engine (FRE) for optical character recognition (OCR), the ABBYY® Flexicapture Engine (FCE) for template-based extraction, ABBYY® Flexicapture for Invoices, document splitting and classification tools, natural language processing (NPL) and rule-based information extraction tools, data annotation for PDF and Word documents, and a continuous learning pipeline for creating machine learning-based information extraction models.

Article Title: Methods and systems for artificial intelligence-assisted document annotation
Article Snippet: The Schedule K-1 prediction process comprises four main steps: (i) the electronic Schedule K-1 documents are processed using the FlexiCapture Engine (FCEng), which combines ABBYY FlexiCapture, ABBYY FineReader, and ABBYY Optical Character Recognition (OCR) capabilities, to produce XML or JTD files; (ii) a trained Statement/Footnote Classifier model segments the text within the document into statement or footnote categories; (iii) a trained Statement Extractor model predicts which text corresponds to the statement labels, and a trained Footnote Extractor model predicts which text corresponds to the footnote labels.

Article Title: GERDA: The German Election Database.
Article Snippet: In several instances (Brandenburg 1993 and 1998; Hamburg 1991, 1993, and 1997; Rhineland-Palatinate 1994 and 1999; and Schleswig-Holstein 1994, 1998, and 2003), we obtained PDFs, which we digitized using the Optical Character Recognition (OCR) editor of ABBYY FineReader.



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