3 books on Intelligent Document Recognition [PDF]

October 24, 2024

Books on Intelligent Document Recognition (IDR) cover a wide array of topics such as optical character recognition (OCR), natural language processing and machine learning algorithms, describing how AI can be used to extract data from unstructured documents efficiently.

1. Intelligent Document Processing: A Guide For Building RPA Solutions
2023 by Lahiru Fernando



"IIntelligent Document Processing: A Guide for Constructing RPA Solutions" is a concise handbook that offers readers valuable insights into optimizing Intelligent Document Understanding solutions integrated into Robotic Process Automation (RPA) workflows. Moreover, this compact guide presents real-world case studies, technical obstacles, best practices, industry trends, references to pertinent external research articles and in-depth discussions focused on the creation of efficient and scalable RPA solutions for intelligent document processing. The book also incorporates the author's firsthand experiences from numerous intelligent document automation projects. This mini-guide serves as an overview of the current technological landscape, offering practical advice and solutions. It is best utilized as a reference manual to support your initiatives in the realm of "Optical AI."
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2. Intelligent Document Capture with Ephesoft
2012 by Ike Kavas, Michael Muller



Crafted in a user-friendly and comprehensible style, this book serves as a comprehensive manual for mastering document capture using Ephesoft. While primarily designed for information technology professionals aiming to implement and set up Ephesoft within their organizations, it also extends its value to anyone seeking to acquire knowledge about document capture practices in a broader context.
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3. Computer-Aided Intelligent Recognition Techniques and Applications
2005 by Dr. Muhammad Sarfraz



The book "Computer-Aided Intelligent Recognition Techniques and Applications" serves as a versatile resource encompassing a broad spectrum of applications across various domains, including IT, education, security, finance, law enforcement, manufacturing, healthcare, multimedia and more. It disseminates knowledge spanning multiple disciplines such as pattern recognition, artificial intelligence, image processing, computer vision, neural networks, cryptography and evolutionary algorithms, among others. This comprehensive guide supplements theoretical concepts with real-world case studies and practical examples. It is a vital reference for computer scientists, engineers and consultants seeking comprehensive insights into the latest advancements in computer-aided intelligent recognition techniques and their diverse applications. Additionally, it is a valuable resource for senior undergraduate and graduate students and professionals involved in the field of intelligent recognition.
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