الصفحة 1
الصفحة 1
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Human interactive proofs ; 2nd International workshop, HIP 2005, Bethlehem, PA, USA, May 19-20, 2005, Proceedings

Constitutes the refereed proceedings of the Second International Workshop on Human Interactive Proofs, HIP 2005, held in Bethlehem, PA, USA in May 2005. This book is devoted to the new class of security protocols called human interactive proofs. It includes sections such as: CAPTCHAs and performance analysis, and HIP architectures.

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Document Analysis Systems VII ; 7th International Workshop, DAS 2006, Nelson, New Zealand, February 13-15, 2006, Proceedings

This book constitutes the refereed proceedings of the 7th International Conference on Document Analysis Systems, DAS 2006, held in Nelson, New Zealand, in February 2006.

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Digital Document Processing : Major Directions and Recent Advances

With the advent of the Digital Library initiative, web document processing and biometric aspects of digital document processing, together with new techniques of printed and handwritten Optical Character Recognition (OCR), a good overview of this fast-developing field is invaluable. In this book, all the major and frontier topics in the field of document analysis are brought together into a single volume creating a unique reference source.

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Markov Models for Pattern Recognition : From Theory to Applications

Describes the underlying theoretical concepts - covering Hidden Markov models and Markov chain models - and presents the techniques and algorithmic solutions essential to creating real world applications. The actual use of Markov models in their three main application areas - namely speech recognition, handwriting recognition, and biological sequence analysis - is presented with examples of successful systems.

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Machine Learning in Document Analysis and Recognition

The objective of Document Analysis and Recognition (DAR) is to recognize the text and graphicalcomponents of a document and to extract information. With ?rst papers dating back to the 1960’s, DAR is a mature but still gr- ing research?eld with consolidated and known techniques. Optical Character Recognition (OCR) engines are some of the most widely recognized pr- ucts of the research in this ?eld, while broader DAR techniques are nowadays studied and applied to other industrial and o?ce automation systems. In the machine learning community, one of the most widely known - search problems addressed in DAR is recognition of unconstrained handwr- ten characters which has been frequently used in the past as a benchmark for evaluating machine learning algorithms, especially supervised classi?ers.

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Machine Learning for Audio, Image and Video Analysis : Theory and Applications

The book is organized in four parts: The first focuses on technical aspects, basic mathematical notions and elementary machine learning techniques. The second provides an extensive survey of most relevant machine learning techniques for media processing, while the third part focuses on applications and shows how techniques are applied in actual problems. The fourth part contains detailed appendices that provide notions about the main mathematical instruments used throughout the text

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Biometric Authentication ; International ECCV 2002 Workshop Copenhagen, Denmark, June 1, 2002 Proceedings

Biometric authentication refers to identifying an individual based on his or her distinguishing physiological and/or behavioral characteristics. It associates an individual with a previously determined identity based on that individual s appearance or behavior. Because many physiological or behavioral characteristics (biometric indicators) are distinctive to each person, biometric identifiers are inherently more reliable and more capable than knowledge-based (e.g., password) and token-based (e.g., a key) techniques in differentiating between an authorized person and a fraudulent impostor. For this reason, more and more organizations are looking to automated identity authentication systems to improve customer satisfaction, security, and operating efficiency as well as to save critical resources.

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Arabic and Chinese Handwriting Recognition ; SACH 2006 Summit College Park, MD, USA, September 27-28, 2006 Selected Papers

Cheriet provides an overview of the problems of Arabic recognition and how systems can use natural language processing techniques to correct errors in lexicon-based systems.

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