Author: Anne S. McCarthy
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 122
Book Description
Image Character Recognition (ICR)
Author: Anne S. McCarthy
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 122
Book Description
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 122
Book Description
Handbook Of Character Recognition And Document Image Analysis
Author: Horst Bunke
Publisher: World Scientific
ISBN: 9814500380
Category : Computers
Languages : en
Pages : 851
Book Description
Optical character recognition and document image analysis have become very important areas with a fast growing number of researchers in the field. This comprehensive handbook with contributions by eminent experts, presents both the theoretical and practical aspects at an introductory level wherever possible.
Publisher: World Scientific
ISBN: 9814500380
Category : Computers
Languages : en
Pages : 851
Book Description
Optical character recognition and document image analysis have become very important areas with a fast growing number of researchers in the field. This comprehensive handbook with contributions by eminent experts, presents both the theoretical and practical aspects at an introductory level wherever possible.
Internal Revenue Bulletin
Author: United States. Internal Revenue Service
Publisher:
ISBN:
Category : Tax administration and procedure
Languages : en
Pages : 988
Book Description
Publisher:
ISBN:
Category : Tax administration and procedure
Languages : en
Pages : 988
Book Description
Internal Revenue Cumulative Bulletin
Author: United States. Internal Revenue Service
Publisher:
ISBN:
Category : Tax administration and procedure
Languages : en
Pages : 1322
Book Description
Publisher:
ISBN:
Category : Tax administration and procedure
Languages : en
Pages : 1322
Book Description
COMPUTER VISION: IMAGE RECOGNITION AND ANALYSIS TECHNIQUES
Author: Prof. Munindra Lunagaria
Publisher: Xoffencerpublication
ISBN: 8196401817
Category : Computers
Languages : en
Pages : 220
Book Description
Computer vision is what we call the practice of using computer-based imaging where there is no human interaction in the visual loop at any point in the process. The photos are analyzed by a computer, which then takes appropriate action depending on their results. Computer vision systems are used in a variety of medical disciplines, and the only thing that can be said with absolute confidence is that the scope of these systems' applications will continue to expand in the future is the only thing that can be declared with absolute certainty. processing one or more digital photographs in order to generate valuable inferences about real-world physical objects and situations by computing the features of the 3D environment. This processing may be done with either one picture or all of them together. generating an accurate and comprehensive description of a real world object based on a photograph of that thing. The discipline of computer vision came into being as a consequence of efforts to model image processing utilizing the several approaches that are accessible within the discipline of machine learning. The field of computer vision makes use of machine learning to search for patterns in images with the end goal of deciphering such patterns. The field of computer vision entails the practice of teaching computers to recognize objects based on the digital still photos or moving movies that are sent into them. Finding methods through which jobs can be automated that now rely on the human visual system is the objective here. Image processing is one of the various methods that are utilized in the execution of this approach. The subfield of artificial intelligence (AI) known as computer vision is an absolutely necessary component in order for computers and other types of systems to be able to respond or provide suggestions based on visual data such as digital photos, movies, and other types of inputs. The same way that artificial intelligence makes it possible for computers to think, computer vision makes it possible for computers to see, comprehend, and observe. Computer vision and human vision are functionally comparable; the primary difference is that human eyesight developed far earlier than computer vision. The capacity of human beings to learn to differentiate between different things, their distances from one another, whether or not the items are moving
Publisher: Xoffencerpublication
ISBN: 8196401817
Category : Computers
Languages : en
Pages : 220
Book Description
Computer vision is what we call the practice of using computer-based imaging where there is no human interaction in the visual loop at any point in the process. The photos are analyzed by a computer, which then takes appropriate action depending on their results. Computer vision systems are used in a variety of medical disciplines, and the only thing that can be said with absolute confidence is that the scope of these systems' applications will continue to expand in the future is the only thing that can be declared with absolute certainty. processing one or more digital photographs in order to generate valuable inferences about real-world physical objects and situations by computing the features of the 3D environment. This processing may be done with either one picture or all of them together. generating an accurate and comprehensive description of a real world object based on a photograph of that thing. The discipline of computer vision came into being as a consequence of efforts to model image processing utilizing the several approaches that are accessible within the discipline of machine learning. The field of computer vision makes use of machine learning to search for patterns in images with the end goal of deciphering such patterns. The field of computer vision entails the practice of teaching computers to recognize objects based on the digital still photos or moving movies that are sent into them. Finding methods through which jobs can be automated that now rely on the human visual system is the objective here. Image processing is one of the various methods that are utilized in the execution of this approach. The subfield of artificial intelligence (AI) known as computer vision is an absolutely necessary component in order for computers and other types of systems to be able to respond or provide suggestions based on visual data such as digital photos, movies, and other types of inputs. The same way that artificial intelligence makes it possible for computers to think, computer vision makes it possible for computers to see, comprehend, and observe. Computer vision and human vision are functionally comparable; the primary difference is that human eyesight developed far earlier than computer vision. The capacity of human beings to learn to differentiate between different things, their distances from one another, whether or not the items are moving
Artificial Neural Networks and Machine Learning -- ICANN 2014
Author: Stefan Wermter
Publisher: Springer
ISBN: 3319111795
Category : Computers
Languages : en
Pages : 874
Book Description
The book constitutes the proceedings of the 24th International Conference on Artificial Neural Networks, ICANN 2014, held in Hamburg, Germany, in September 2014. The 107 papers included in the proceedings were carefully reviewed and selected from 173 submissions. The focus of the papers is on following topics: recurrent networks; competitive learning and self-organisation; clustering and classification; trees and graphs; human-machine interaction; deep networks; theory; reinforcement learning and action; vision; supervised learning; dynamical models and time series; neuroscience; and applications.
Publisher: Springer
ISBN: 3319111795
Category : Computers
Languages : en
Pages : 874
Book Description
The book constitutes the proceedings of the 24th International Conference on Artificial Neural Networks, ICANN 2014, held in Hamburg, Germany, in September 2014. The 107 papers included in the proceedings were carefully reviewed and selected from 173 submissions. The focus of the papers is on following topics: recurrent networks; competitive learning and self-organisation; clustering and classification; trees and graphs; human-machine interaction; deep networks; theory; reinforcement learning and action; vision; supervised learning; dynamical models and time series; neuroscience; and applications.
FBI Law Enforcement Bulletin
Data Science and Emerging Technologies
Author: Yap Bee Wah
Publisher: Springer Nature
ISBN: 9819907411
Category : Technology & Engineering
Languages : en
Pages : 562
Book Description
The book presents selected papers from International Conference on Data Science and Emerging Technologies (DaSET 2022), held online at UNITAR International University, Malaysia, during December 20–21, 2022. This book aims to present current research and applications of data science and emerging technologies. The deployment of data science and emerging technology contributes to the achievement of the Sustainable Development Goals for social inclusion, environmental sustainability, and economic prosperity. Data science and emerging technologies such as artificial intelligence and blockchain are useful for various domains such as marketing, health care, finance, banking, environmental, and agriculture. An important grand challenge in data science is to determine how developments in computational and social-behavioral sciences can be combined to improve well-being, emergency response, sustainability, and civic engagement in a well-informed, data-driven society. The topics of this book include, but not limited to: artificial intelligence, big data technology, machine and deep learning, data mining, optimization algorithms, blockchain, Internet of Things (IoT), cloud computing, computer vision, cybersecurity, augmented and virtual reality, cryptography, and statistical learning.
Publisher: Springer Nature
ISBN: 9819907411
Category : Technology & Engineering
Languages : en
Pages : 562
Book Description
The book presents selected papers from International Conference on Data Science and Emerging Technologies (DaSET 2022), held online at UNITAR International University, Malaysia, during December 20–21, 2022. This book aims to present current research and applications of data science and emerging technologies. The deployment of data science and emerging technology contributes to the achievement of the Sustainable Development Goals for social inclusion, environmental sustainability, and economic prosperity. Data science and emerging technologies such as artificial intelligence and blockchain are useful for various domains such as marketing, health care, finance, banking, environmental, and agriculture. An important grand challenge in data science is to determine how developments in computational and social-behavioral sciences can be combined to improve well-being, emergency response, sustainability, and civic engagement in a well-informed, data-driven society. The topics of this book include, but not limited to: artificial intelligence, big data technology, machine and deep learning, data mining, optimization algorithms, blockchain, Internet of Things (IoT), cloud computing, computer vision, cybersecurity, augmented and virtual reality, cryptography, and statistical learning.
Implementing Document Imaging and Capture Solutions with IBM Datacap
Author: Whei-Jen Chen
Publisher: IBM Redbooks
ISBN: 0738440906
Category : Computers
Languages : en
Pages : 352
Book Description
Organizations face many challenges in managing ever-increasing documents that they need to conduct their businesses. IBM® content management and imaging solutions can capture, store, manage, integrate, and deliver various forms of content throughout an enterprise. These tools can help reduce costs associated with content management and help organizations deliver improved customer service. The advanced document capture capabilities are provided through IBM Datacap software. This IBM Redbooks® publication focuses on Datacap components, system architecture, functions, and capabilities. It explains how Datacap works, how to design a document image capture solution, and how to implement the solution using Datacap Developer Tools, such as Datacap FastDoc (Admin). FastDoc is the development tool that designers use to create rules and rule sets, configure a document hierarchy and task profiles, and set up a verification panel for image verification. A loan application example explains the advanced technologies of IBM Datacap Version 9. This scenario shows how to develop a versatile capture solution that is able to handle both structured and unstructured documents. Information about high availability, scalability, performance, backup and recovery options, preferable practices, and suggestions for designing and implementing an imaging solution is also included. This book is intended for IT architects and professionals who are responsible for creating, improving, designing, and implementing document imaging solutions for their organizations.
Publisher: IBM Redbooks
ISBN: 0738440906
Category : Computers
Languages : en
Pages : 352
Book Description
Organizations face many challenges in managing ever-increasing documents that they need to conduct their businesses. IBM® content management and imaging solutions can capture, store, manage, integrate, and deliver various forms of content throughout an enterprise. These tools can help reduce costs associated with content management and help organizations deliver improved customer service. The advanced document capture capabilities are provided through IBM Datacap software. This IBM Redbooks® publication focuses on Datacap components, system architecture, functions, and capabilities. It explains how Datacap works, how to design a document image capture solution, and how to implement the solution using Datacap Developer Tools, such as Datacap FastDoc (Admin). FastDoc is the development tool that designers use to create rules and rule sets, configure a document hierarchy and task profiles, and set up a verification panel for image verification. A loan application example explains the advanced technologies of IBM Datacap Version 9. This scenario shows how to develop a versatile capture solution that is able to handle both structured and unstructured documents. Information about high availability, scalability, performance, backup and recovery options, preferable practices, and suggestions for designing and implementing an imaging solution is also included. This book is intended for IT architects and professionals who are responsible for creating, improving, designing, and implementing document imaging solutions for their organizations.
Learn Computer Vision Using OpenCV
Author: Sunila Gollapudi
Publisher: Apress
ISBN: 1484242610
Category : Computers
Languages : en
Pages : 163
Book Description
Build practical applications of computer vision using the OpenCV library with Python. This book discusses different facets of computer vision such as image and object detection, tracking and motion analysis and their applications with examples. The author starts with an introduction to computer vision followed by setting up OpenCV from scratch using Python. The next section discusses specialized image processing and segmentation and how images are stored and processed by a computer. This involves pattern recognition and image tagging using the OpenCV library. Next, you’ll work with object detection, video storage and interpretation, and human detection using OpenCV. Tracking and motion is also discussed in detail. The book also discusses creating complex deep learning models with CNN and RNN. The author finally concludes with recent applications and trends in computer vision. After reading this book, you will be able to understand and implement computer vision and its applications with OpenCV using Python. You will also be able to create deep learning models with CNN and RNN and understand how these cutting-edge deep learning architectures work. What You Will LearnUnderstand what computer vision is, and its overall application in intelligent automation systems Discover the deep learning techniques required to build computer vision applications Build complex computer vision applications using the latest techniques in OpenCV, Python, and NumPy Create practical applications and implementations such as face detection and recognition, handwriting recognition, object detection, and tracking and motion analysis Who This Book Is ForThose who have a basic understanding of machine learning and Python and are looking to learn computer vision and its applications.
Publisher: Apress
ISBN: 1484242610
Category : Computers
Languages : en
Pages : 163
Book Description
Build practical applications of computer vision using the OpenCV library with Python. This book discusses different facets of computer vision such as image and object detection, tracking and motion analysis and their applications with examples. The author starts with an introduction to computer vision followed by setting up OpenCV from scratch using Python. The next section discusses specialized image processing and segmentation and how images are stored and processed by a computer. This involves pattern recognition and image tagging using the OpenCV library. Next, you’ll work with object detection, video storage and interpretation, and human detection using OpenCV. Tracking and motion is also discussed in detail. The book also discusses creating complex deep learning models with CNN and RNN. The author finally concludes with recent applications and trends in computer vision. After reading this book, you will be able to understand and implement computer vision and its applications with OpenCV using Python. You will also be able to create deep learning models with CNN and RNN and understand how these cutting-edge deep learning architectures work. What You Will LearnUnderstand what computer vision is, and its overall application in intelligent automation systems Discover the deep learning techniques required to build computer vision applications Build complex computer vision applications using the latest techniques in OpenCV, Python, and NumPy Create practical applications and implementations such as face detection and recognition, handwriting recognition, object detection, and tracking and motion analysis Who This Book Is ForThose who have a basic understanding of machine learning and Python and are looking to learn computer vision and its applications.