Download or read book Optical Character Recognition Using Neural Network written by David T. Au and published by . This book was released on 1993 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Optical Character Recognition Systems for Different Languages with Soft Computing written by Arindam Chaudhuri and published by Springer. This book was released on 2016-12-23 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book offers a comprehensive survey of soft-computing models for optical character recognition systems. The various techniques, including fuzzy and rough sets, artificial neural networks and genetic algorithms, are tested using real texts written in different languages, such as English, French, German, Latin, Hindi and Gujrati, which have been extracted by publicly available datasets. The simulation studies, which are reported in details here, show that soft-computing based modeling of OCR systems performs consistently better than traditional models. Mainly intended as state-of-the-art survey for postgraduates and researchers in pattern recognition, optical character recognition and soft computing, this book will be useful for professionals in computer vision and image processing alike, dealing with different issues related to optical character recognition.
Download or read book Optical character recognition using neural networks written by Theodor Constantinescu and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book 2017 International Conference on Computer Communication and Informatics ICCCI written by IEEE Staff and published by . This book was released on 2017-01-05 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The 2017 International Conference on Computer Communication and Informatics (ICCCI) aims to provide an outstanding opportunity for both academic and industrial communities alike to address new trends and challenges and emerging technologies on topics relevant to today s fast moving areas of Computer, Communication and Informatics The conference will feature invited talks and referred paper presentations The vision of ICCCI is to develop foster communication among researchers and practitioners working in a wide variety of areas in communication and informatics with a common interest
Download or read book Optical Character Recognition Using Neural Networks written by Chih-Chin Yang and published by . This book was released on 1994 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Optical Character Recognition Using Neural Network Co processor Board written by Jehad Ibraheem Sahawneh and published by . This book was released on 1993 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Character Recognition Systems written by Mohamed Cheriet and published by John Wiley & Sons. This book was released on 2007-11-27 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Much of pattern recognition theory and practice, including methods such as Support Vector Machines, has emerged in an attempt to solve the character recognition problem. This book is written by very well-known academics who have worked in the field for many years and have made significant and lasting contributions. The book will no doubt be of value to students and practitioners." -Sargur N. Srihari, SUNY Distinguished Professor, Department of Computer Science and Engineering, and Director, Center of Excellence for Document Analysis and Recognition (CEDAR), University at Buffalo, The State University of New York "The disciplines of optical character recognition and document image analysis have a history of more than forty years. In the last decade, the importance and popularity of these areas have grown enormously. Surprisingly, however, the field is not well covered by any textbook. This book has been written by prominent leaders in the field. It includes all important topics in optical character recognition and document analysis, and is written in a very coherent and comprehensive style. This book satisfies an urgent need. It is a volume the community has been awaiting for a long time, and I can enthusiastically recommend it to everybody working in the area." -Horst Bunke, Professor, Institute of Computer Science and Applied Mathematics (IAM), University of Bern, Switzerland In Character Recognition Systems, the authors provide practitioners and students with the fundamental principles and state-of-the-art computational methods of reading printed texts and handwritten materials. The information presented is analogous to the stages of a computer recognition system, helping readers master the theory and latest methodologies used in character recognition in a meaningful way. This book covers: * Perspectives on the history, applications, and evolution of Optical Character Recognition (OCR) * The most widely used pre-processing techniques, as well as methods for extracting character contours and skeletons * Evaluating extracted features, both structural and statistical * Modern classification methods that are successful in character recognition, including statistical methods, Artificial Neural Networks (ANN), Support Vector Machines (SVM), structural methods, and multi-classifier methods * An overview of word and string recognition methods and techniques * Case studies that illustrate practical applications, with descriptions of the methods and theories behind the experimental results Each chapter contains major steps and tricks to handle the tasks described at-hand. Researchers and graduate students in computer science and engineering will find this book useful for designing a concrete system in OCR technology, while practitioners will rely on it as a valuable resource for the latest advances and modern technologies that aren't covered elsewhere in a single book.
Download or read book Proceedings of the 3rd International Conference on Frontiers of Intelligent Computing Theory and Applications FICTA 2014 written by Suresh Chandra Satapathy and published by Springer. This book was released on 2014-10-31 with total page 783 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains 87 papers presented at FICTA 2014: Third International Conference on Frontiers in Intelligent Computing: Theory and Applications. The conference was held during 14-15, November, 2014 at Bhubaneswar, Odisha, India. This volume contains papers mainly focused on Network and Information Security, Grid Computing and Clod Computing, Cyber Security and Digital Forensics, Computer Vision, Signal, Image & Video Processing, Software Engineering in Multidisciplinary Domains and Ad-hoc and Wireless Sensor Networks.
Download or read book Context Sensitive Optical Character Recognition Using Neural Networks and Hidden Markov Models written by Steven C. Elliott and published by . This book was released on 1992 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "This thesis investigates a method for using contextual information in text recognition. This is based on the premise that, while reading, humans recognize words with missing or garbled characters by examining the surrounding characters and then selecting the appropriate character. The correct character is chosen based on an inherent knowledge of the language and spelling techniques. We can then model this statistically. The approach taken by this Thesis is to combine feature extraction techniques, Neural Networks and Hidden Markov Modeling. This method of character recognition involves a three step process: pixel image preprocessing, neural network classification and context interpretation. Pixel image preprocessing applies a feature extraction algorithm to original bit mapped images, which produces a feature vector for the original images which are input into a neural network. The neural network performs the initial classification of the characters by producing ten weights, one for each character. The magnitude of the weight is translated into the confidence the network has in each of the choices. The greater the magnitude and separation, the more confident the neural network is of a given choice. The output of the neural network is the input for a context interpreter. The context interpreter uses Hidden Markov Modeling (HMM) techniques to determine the most probable classification for all characters based on the characters that precede that character and character pair statistics. The HMMs are built using an a priori knowledge of the language: a statistical description of the probabilities of digrams. Experimentation and verification of this method combines the development and use of a preprocessor program, a Cascade Correlation Neural Network and a HMM context interpreter program. Results from these experiments show the neural network successfully classified 88.2 percent of the characters. Expanding this to the word level, 63 percent of the words were correctly identified. Adding the Hidden Markov Modeling improved the word recognition to 82.9 percent."--Abstract.
Download or read book Optical Character Recognition written by Stephen V. Rice and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optical character recognition (OCR) is the most prominent and successful example of pattern recognition to date. There are thousands of research papers and dozens of OCR products. Optical Character Rcognition: An Illustrated Guide to the Frontier offers a perspective on the performance of current OCR systems by illustrating and explaining actual OCR errors. The pictures and analysis provide insight into the strengths and weaknesses of current OCR systems, and a road map to future progress. Optical Character Recognition: An Illustrated Guide to the Frontier will pique the interest of users and developers of OCR products and desktop scanners, as well as teachers and students of pattern recognition, artificial intelligence, and information retrieval. The first chapter compares the character recognition abilities of humans and computers. The next four chapters present 280 illustrated examples of recognition errors, in a taxonomy consisting of Imaging Defects, Similar Symbols, Punctuation, and Typography. These examples were drawn from large-scale tests conducted by the authors. The final chapter discusses possible approaches for improving the accuracy of today's systems, and is followed by an annotated bibliography. Optical Character Recognition: An Illustrated Guide to the Frontier is suitable as a secondary text for a graduate level course on pattern recognition, artificial intelligence, and information retrieval, and as a reference for researchers and practitioners in industry.
Download or read book Neural Networks in Telecommunications written by Ben Yuhas and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural Networks in Telecommunications consists of a carefully edited collection of chapters that provides an overview of a wide range of telecommunications tasks being addressed with neural networks. These tasks range from the design and control of the underlying transport network to the filtering, interpretation and manipulation of the transported media. The chapters focus on specific applications, describe specific solutions and demonstrate the benefits that neural networks can provide. By doing this, the authors demonstrate that neural networks should be another tool in the telecommunications engineer's toolbox. Neural networks offer the computational power of nonlinear techniques, while providing a natural path to efficient massively-parallel hardware implementations. In addition, the ability of neural networks to learn allows them to be used on problems where straightforward heuristic or rule-based solutions do not exist. Together these capabilities mean that neural networks offer unique solutions to problems in telecommunications. For engineers and managers in telecommunications, Neural Networks in Telecommunications provides a single point of access to the work being done by leading researchers in this field, and furnishes an in-depth description of neural network applications.
Download or read book Handbook of Character Recognition and Document Image Analysis written by Horst Bunke and published by World Scientific. This book was released on 1997 with total page 868 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Deep Learning written by Siddhartha Bhattacharyya and published by Walter de Gruyter GmbH & Co KG. This book was released on 2020-06-22 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the fundamentals of deep learning along with reporting on the current state-of-art research on deep learning. In addition, it provides an insight of deep neural networks in action with illustrative coding examples. Deep learning is a new area of machine learning research which has been introduced with the objective of moving ML closer to one of its original goals, i.e. artificial intelligence. Deep learning was developed as an ML approach to deal with complex input-output mappings. While traditional methods successfully solve problems where final value is a simple function of input data, deep learning techniques are able to capture composite relations between non-immediately related fields, for example between air pressure recordings and English words, millions of pixels and textual description, brand-related news and future stock prices and almost all real world problems. Deep learning is a class of nature inspired machine learning algorithms that uses a cascade of multiple layers of nonlinear processing units for feature extraction and transformation. Each successive layer uses the output from the previous layer as input. The learning may be supervised (e.g. classification) and/or unsupervised (e.g. pattern analysis) manners. These algorithms learn multiple levels of representations that correspond to different levels of abstraction by resorting to some form of gradient descent for training via backpropagation. Layers that have been used in deep learning include hidden layers of an artificial neural network and sets of propositional formulas. They may also include latent variables organized layer-wise in deep generative models such as the nodes in deep belief networks and deep boltzmann machines. Deep learning is part of state-of-the-art systems in various disciplines, particularly computer vision, automatic speech recognition (ASR) and human action recognition.
Download or read book The History of OCR Optical Character Recognition written by Herbert F. Schantz and published by . This book was released on 1982 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Optical Character Recognition in the Historical Discipline written by Netherlands Historical Data Archive and published by . This book was released on 1993 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Optical character recognition via neural networks written by Jason Moix and published by . This book was released on 2015 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Neural Network Optical Character Recognition System written by Jie Li and published by . This book was released on 1990 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt:
