pattern recognition

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Pattern Recognition
Author :
Publisher : Penguin UK
Release Date :
ISBN 10 : 0141904461
Pages : 368 pages
Rating : 3.5/5 (84 users)
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One of the most influential and imaginative sci-fi writers turns his attention to London - with dazzling results. 'Part-detective story, part-cultural snapshot . . . all bound by Gibson's pin-sharp prose' Arena ________________________ Cayce Pollard owes her living to her pathological sensitivity to logos. In London to consult for the world's coolest ad agency, she finds herself catapulted, via her addiction to a mysterious body of fragmentary film footage, uploaded to the Web by a shadowy auteur, into a global quest for this unknown "garage Kubrick". Cayce becomes involved with an eccentric hacker, a vengeful ad executive, a defrocked mathematician, a Tokyo Otaku-coven known as Eye of the Dragon and, eventually, the elusive Kubrick himself. William Gibson's novel is about the eternal mystery of London, the coolest sneakers in the world, and life in (the former) USSR. ________________________ 'A compelling, humane story with a sympathetic heroine searching for meaning and consolation in a post-everything world' Daily Telegraph 'A big novel, full of bold ideas . . . races along like an expert thriller' GQ 'It's dialogue and characterization will amaze you. A wonderfully detailed, reckless journey of espionage and lies' USA Today 'Electric, profound. Gibson's descriptions of Tokyo, Russia and London are surreally spot-on' Financial Times

Pattern Recognition

One of the most influential and imaginative sci-fi writers turns his attention to London - with dazzling results. 'Part-detective story, part-cultural snapshot . . . all bound by Gibson's pin-sharp prose' Arena ________________________ Cayce Pollard owes her living to her pathological sensitivity to logos. In London to consult for the world's coolest ad agency,

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Pattern Recognition

“Pattern Recognition is William Gibson’s best book since he rewrote all the rules in Neuromancer.”—Neil Gaiman, author of American Gods “One of the first authentic and vital novels of the 21st century.”—The Washington Post Book World The accolades and acclaim are endless for William Gibson's coast-to-coast bestseller.

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Pattern Recognition

CD-ROM contains: Datasets -- Software tools.

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Pattern Recognition and Machine Learning

This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning.

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Pattern Recognition

This book constitutes the refereed proceedings of the 28th Symposium of the German Association for Pattern Recognition, DAGM 2006. The book presents 32 revised full papers and 44 revised poster papers together with 5 invited papers. Topical sections include image filtering, restoration and segmentation, shape analysis and representation, recognition, categorization and detection, computer vision

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Pattern Recognition

This book constitutes the proceedings of the 13th Mexican Conference on Pattern Recognition, MCPR 2021, which was planned to be held in Mexico City, Mexico, in June 2021. The conference was instead held virtually. The 35 papers presented in this volume were carefully reviewed and selected from 75 submissions. They are organized in the

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Neural Networks for Pattern Recognition

`Readers will emerge with a rigorous statistical grounding in the theory of how to construct and train neural networks in pattern recognition' New Scientist

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Pattern Recognition

Pattern recognition is a fast growing area with applications in a widely diverse number of fields such as communications engineering, bioinformatics, data mining, content-based database retrieval, to name but a few. This new edition addresses and keeps pace with the most recent advancements in these and related areas. This new

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Pattern Recognition and Machine Learning

This is the first text on pattern recognition to present the Bayesian viewpoint, one that has become increasing popular in the last five years. It presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It provides the first text to use graphical

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Image Processing and Pattern Recognition

Image Processing and Pattern Recognition covers major applications in the field, including optical character recognition, speech classification, medical imaging, paper currency recognition, classification reliability techniques, and sensor technology. The text emphasizes algorithms and architectures for achieving practical and effective systems, and presents many examples. Practitioners, researchers, and students in computer

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Pattern Recognition

Pattern Recognition: Techniques and Applications introduces the concept of inductive learning and provides an exhaustive coverage of the procedures for Pattern Recognition. The book would serve as a textbook for senior undergraduate and master's engineering students. Written in a lucid and student-friendly style, the text encourages self-study and instils working

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Pattern Recognition and Neural Networks

This 1996 book explains the statistical framework for pattern recognition and machine learning, now in paperback.

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Pattern Recognition with Fuzzy Objective Function Algorithms

The fuzzy set was conceived as a result of an attempt to come to grips with the problem of pattern recognition in the context of imprecisely defined categories. In such cases, the belonging of an object to a class is a matter of degree, as is the question of whether

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Pattern Recognition and Data Mining

The two volume set LNCS 3686 and LNCS 3687 constitutes the refereed proceedings of the Third International Conference on Advances in Pattern Recognition, ICAPR 2005, held in Bath, UK in August 2005. The papers submitted to ICAPR 2005 were thoroughly reviewed by up to three referees per paper and less than 40% of the submitted papers

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Pattern Recognition Principles

Decision functions. Pattern classification by distance functions. Pattern classification by likelihood functions. Trainable pattern classifiers-the deterministic approach. Trainable pattern classifiers - the statistical approach. Pattern preprocessing and feature selection. Syntatic pattern recognition. Bibliography. Index.

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