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Applied Pattern Recognition by Horst Bunke (47 results)
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Condition: Good. Volume 91. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,650grams, ISBN:9783540768302.
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Condition: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
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Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
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Applied Pattern Recognition (Studies in Computational Intelligence, 91)
Seller: Phatpocket Limited, Waltham Abbey, HERTS, United Kingdom
Seller rating 5 out of 5 stars
Condition: Like New. Used - Like New. Book is new and unread but may have minor shelf wear. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.
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Condition: New. pp. xii + 246 1st Edition.
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Condition: New. pp. xii + 246.
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Applied Graph Theory in Computer Vision and Pattern Recognition (Studies in Computational Intelligence, 52)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 96.15
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
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Condition: New.
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Applied Graph Theory in Computer Vision and Pattern Recognition
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Condition: New. pp. xii + 246.
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Applied Graph Theory in Computer Vision and Pattern Recognition
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
£ 104.39
£ 15 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: As New. Unread book in perfect condition.
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Condition: New. pp. 276.
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Condition: New. pp. 276.
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Applied Pattern Recognition (Studies in Computational Intelligence, 91)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 116.47
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
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Applied Graph Theory in Computer Vision and Pattern Recognition
Seller: Scarthin Books ABA, ILAB., Cromford, United Kingdom
Seller rating 5 out of 5 stars
First Edition
Book Hardcover. Condition: As New. No Jacket. 1st Edition. Springer, 2007. 1st Edition . As New/No Jacket. Book still in original shrink-wrap.
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Condition: As New. Unread book in perfect condition.
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Applied Graph Theory in Computer Vision and Pattern Recognition (Studies in Computational Intelligence)
Language: English
Published by Springer Berlin Heidelberg, 2007
ISBN 10: 3642087647 ISBN 13: 9783642087646
Paperback. Condition: Brand New. 276 pages. 9.25x6.10x0.63 inches. In Stock.
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Applied Graph Theory in Computer Vision and Pattern Recognition
Language: English
Published by Springer Berlin Heidelberg, 2007
ISBN 10: 3540680195 ISBN 13: 9783540680192
Gebunden. Condition: New. Will serve as a foundation for a variety of useful applications of the graph theory to computer vision, pattern recognition, and related areasCovers a representative set of novel graph-theoretic methods for complex computer vision and pattern reco.
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Applied Graph Theory in Computer Vision and Pattern Recognition
Language: English
Published by Springer, Springer Spektrum, 2010
ISBN 10: 3642087647 ISBN 13: 9783642087646
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Graph theory has strong historical roots in mathematics, especially in topology. Its birth is usually associated with the 'four-color problem' posed by Francis Guthrie 1 in 1852, but its real origin probably goes back to the Seven Bridges of Konigsber g 2 problem proved by Leonhard Euler in 1736. A computational solution to these two completely different problems could be found after each problem was abstracted to the level of a graph model while ignoring such irrelevant details as country shapes or cross-river distances. In general, a graph is a nonempty set of points (vertices) and the most basic information preserved by any graph structure refers to adjacency relationships (edges) between some pairs of points. In the simplest graphs, edges do not have to hold any attributes, except their endpoints, but in more sophisticated graph structures, edges can be associated with a direction or assigned a label. Graph vertices can be labeled as well. A graph can be represented graphically as a drawing (vertex=dot,edge=arc),but,aslongaseverypairofadjacentpointsstaysconnected by the same edge, the graph vertices can be moved around on a drawing without changing the underlying graph structure. The expressive power of the graph models placing a special emphasis on c- nectivity between objects has made them the models of choice in chemistry, physics, biology, and other elds.
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Applied Graph Theory in Computer Vision and Pattern Recognition (Studies in Computational Intelligence, 52)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 136.79
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
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Applied Graph Theory in Computer Vision and Pattern Recognition
Language: English
Published by Springer, Berlin, Springer, 2007
ISBN 10: 3540680195 ISBN 13: 9783540680192
Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Graph theory has strong historical roots in mathematics, especially in topology. Its birth is usually associated with the 'four-color problem' posed by Francis Guthrie 1 in 1852, but its real origin probably goes back to the Seven Bridges of Konigsber g 2 problem proved by Leonhard Euler in 1736. A computational solution to these two completely different problems could be found after each problem was abstracted to the level of a graph model while ignoring such irrelevant details as country shapes or cross-river distances. In general, a graph is a nonempty set of points (vertices) and the most basic information preserved by any graph structure refers to adjacency relationships (edges) between some pairs of points. In the simplest graphs, edges do not have to hold any attributes, except their endpoints, but in more sophisticated graph structures, edges can be associated with a direction or assigned a label. Graph vertices can be labeled as well. A graph can be represented graphically as a drawing (vertex=dot,edge=arc),but,aslongaseverypairofadjacentpointsstaysconnected by the same edge, the graph vertices can be moved around on a drawing without changing the underlying graph structure. The expressive power of the graph models placing a special emphasis on c- nectivity between objects has made them the models of choice in chemistry, physics, biology, and other elds.
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Hardcover. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Condition: New. pp. 260.
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Paperback. Condition: Like New. Like New. book.
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Paperback. Condition: Like New. Like New. book.
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Applied Pattern Recognition
Language: English
Published by Springer Berlin Heidelberg, Springer Berlin Heidelberg, 2010
ISBN 10: 3642095542 ISBN 13: 9783642095542
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - A sharp increase in the computing power of modern computers, accompanied by a decrease in the data storage costs, has triggered the development of extremely powerful algorithms that can analyze complex patterns in large amounts of data within a very short period of time. Consequently, it has become possible to apply pattern recognition techniques to new tasks characterized by tight real-time requirements (e.g., person identification) and/or high complexity of raw data (e.g., clustering trajectories of mobile objects). The main goal of this book is to cover some of the latest application domains of pattern recognition while presenting novel techniques that have been developed or customized in those domains.
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - A sharp increase in the computing power of modern computers, accompanied by a decrease in the data storage costs, has triggered the development of extremely powerful algorithms that can analyze complex patterns in large amounts of data within a very short period of time. Consequently, it has become possible to apply pattern recognition techniques to new tasks characterized by tight real-time requirements (e.g., person identification) and/or high complexity of raw data (e.g., clustering trajectories of mobile objects). The main goal of this book is to cover some of the latest application domains of pattern recognition while presenting novel techniques that have been developed or customized in those domains.
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Condition: new. Questo è un articolo print on demand.
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Condition: new. Questo è un articolo print on demand.
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Applied Graph Theory in Computer Vision and Pattern Recognition
Language: English
Published by Springer, Berlin, Springer Berlin Heidelberg, Springer, 2007
ISBN 10: 3540680195 ISBN 13: 9783540680192
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Graph theory has strong historical roots in mathematics, especially in topology. Its birth is usually associated with the 'four-color problem' posed by Francis Guthrie 1 in 1852, but its real origin probably goes back to the Seven Bridges of Konigsber g 2 problem proved by Leonhard Euler in 1736. A computational solution to these two completely different problems could be found after each problem was abstracted to the level of a graph model while ignoring such irrelevant details as country shapes or cross-river distances. In general, a graph is a nonempty set of points (vertices) and the most basic information preserved by any graph structure refers to adjacency relationships (edges) between some pairs of points. In the simplest graphs, edges do not have to hold any attributes, except their endpoints, but in more sophisticated graph structures, edges can be associated with a direction or assigned a label. Graph vertices can be labeled as well. A graph can be represented graphically as a drawing (vertex=dot,edge=arc),but,aslongaseverypairofadjacentpointsst aysconnected by the same edge, the graph vertices can be moved around on a drawing without changing the underlying graph structure. The expressive power of the graph models placing a special emphasis on c- nectivity between objects has made them the models of choice in chemistry, physics, biology, and other elds. 266 pp. Englisch.
