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Condition: Fair. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In fair condition, suitable as a study copy. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,850grams, ISBN:0121743500.
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Graph Theory: An Algorithmic Approach . Computer science and applied mathematics.
Published by Academic Press. 1975., 1975
£ 16.09
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Add to basketCondition: Gebraucht / Used. Hardcover. Very good. Xv,400pp.
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Applied Graph Theory in Computer Vision and Pattern Recognition
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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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
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£ 90.46
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Applied Graph Theory in Computer Vision and Pattern Recognition
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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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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Applied Graph Theory in Computer Vision and Pattern Recognition
Published by Springer Berlin Heidelberg, 2010
ISBN 10: 3642087647 ISBN 13: 9783642087646
Language: English
£ 95.61
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Add to basketTaschenbuch. 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
Published by Springer, Berlin, Springer Berlin Heidelberg, Springer, 2007
ISBN 10: 3540680195 ISBN 13: 9783540680192
Language: English
£ 99.67
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Add to basketBuch. 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
Published by Springer Berlin Heidelberg, Springer Berlin Heidelberg Nov 2010, 2010
ISBN 10: 3642087647 ISBN 13: 9783642087646
Language: English
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
£ 95.61
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Add to basketTaschenbuch. Condition: Neu. 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,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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 276 pp. Englisch.
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Applied Graph Theory in Computer Vision and Pattern Recognition
Published by Springer Berlin Heidelberg, 2007
ISBN 10: 3540680195 ISBN 13: 9783540680192
Language: English
£ 106.02
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Add to basketGebunden. 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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£ 128.36
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Add to basketCondition: New. pp. 276.
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Applied Graph Theory in Computer Vision and Pattern Recognition (Studies in Computational Intelligence)
Published by Springer Berlin Heidelberg, 2007
ISBN 10: 3642087647 ISBN 13: 9783642087646
Language: English
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 (Studies in Computational Intelligence, 52)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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£ 139.22
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£ 89.43
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Add to baskethardcover. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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Hardcover. Condition: Like New. Like New. book.
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Paperback. Condition: Like New. Like New. book.
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Applied Graph Theory in Computer Vision and Pattern Recognition
Published by Springer Berlin Heidelberg, 2010
ISBN 10: 3642087647 ISBN 13: 9783642087646
Language: English
£ 82.46
Convert currency£ 21.68 shipping from Germany to United KingdomQuantity: Over 20 available
Add to basketCondition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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
Published by Springer, Berlin, Springer Berlin Heidelberg, Springer, 2007
ISBN 10: 3540680195 ISBN 13: 9783540680192
Language: English
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
£ 95.61
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Add to basketBuch. 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.
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Applied Graph Theory in Computer Vision and Pattern Recognition
Published by Springer Berlin Heidelberg Nov 2010, 2010
ISBN 10: 3642087647 ISBN 13: 9783642087646
Language: English
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
£ 95.61
Convert currency£ 9.54 shipping from Germany to United KingdomQuantity: 2 available
Add to basketTaschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents novel graph-theoretic methods for complex computer vision and pattern recognition tasks. It presents the application of graph theory to low-level processing of digital images, presents graph-theoretic learning algorithms for high-level computer vision and pattern recognition applications, and provides detailed descriptions of several applications of graph-based methods to real-world pattern recognition tasks. 276 pp. Englisch.
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Condition: New. Print on Demand pp. 276 Illus.
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£ 141.77
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Add to basketCondition: New. PRINT ON DEMAND pp. 276.
