Book by None
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Any task that involves decision-making can benefit from soft computing techniques which allow premature decisions to be deferred. The processing and analysis of images is no exception to this rule. In the classical image analysis paradigm, the first step is nearly always some sort of segmentation process in which the image is divided into (hopefully, meaningful) parts. It was pointed out nearly 30 years ago by Prewitt (1] that the decisions involved in image segmentation could be postponed by regarding the image parts as fuzzy, rather than crisp, subsets of the image. It was also realized very early that many basic properties of and operations on image subsets could be extended to fuzzy subsets; for example, the classic paper on fuzzy sets by Zadeh [2] discussed the "set algebra" of fuzzy sets (using sup for union and inf for intersection), and extended the defmition of convexity to fuzzy sets. These and similar ideas allowed many of the methods of image analysis to be generalized to fuzzy image parts. For are cent review on geometric description of fuzzy sets see, e. g. , [3]. Fuzzy methods are also valuable in image processing and coding, where learning processes can be important in choosing the parameters of filters, quantizers, etc.
The volume provides a collection of 21 articles containing new material and describing, in a unified way with extensive real life applications, the merits and significance of performing different image processing/analysis tasks in soft computing paradigm. The articles, written by leading experts all over the world, demonstrate the various ways the fuzzy logic, artificial neural networks, genetic algorithms and fractals can be used independently and in integrated manner to provide efficient and flexible information processing capabilities in a stronger computational paradigm for handling the tasks like filtering, edge detection, segmentation, compression , classification, motion estimation, character regognition and target identification. Application domain includes, among others, data mining, computer vision, pattern recognition and machine learning, information technology, remote sensing, forensic investigation, video abstraction and knowledge based systems.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
Gratis für den Versand innerhalb von/der USA
Versandziele, Kosten & DauerEUR 3,52 für den Versand innerhalb von/der USA
Versandziele, Kosten & DauerAnbieter: Books Puddle, New York, NY, USA
Zustand: New. pp. 612. Bestandsnummer des Verkäufers 262178914
Anzahl: 1 verfügbar
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
Zustand: New. pp. 612 Illus. Bestandsnummer des Verkäufers 5669053
Anzahl: 1 verfügbar
Anbieter: ThriftBooks-Dallas, Dallas, TX, USA
Hardcover. Zustand: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less 2.26. Bestandsnummer des Verkäufers G3790812684I4N00
Anzahl: 1 verfügbar
Anbieter: Biblios, Frankfurt am main, HESSE, Deutschland
Zustand: New. pp. 612. Bestandsnummer des Verkäufers 182178920
Anzahl: 1 verfügbar
Anbieter: Lucky's Textbooks, Dallas, TX, USA
Zustand: New. Bestandsnummer des Verkäufers ABLIING23Apr0316110061092
Anzahl: Mehr als 20 verfügbar
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
Zustand: New. In. Bestandsnummer des Verkäufers ria9783790812688_new
Anzahl: Mehr als 20 verfügbar
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Buch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Any task that involves decision-making can benefit from soft computing techniques which allow premature decisions to be deferred. The processing and analysis of images is no exception to this rule. In the classical image analysis paradigm, the first step is nearly always some sort of segmentation process in which the image is divided into (hopefully, meaningful) parts. It was pointed out nearly 30 years ago by Prewitt (1] that the decisions involved in image segmentation could be postponed by regarding the image parts as fuzzy, rather than crisp, subsets of the image. It was also realized very early that many basic properties of and operations on image subsets could be extended to fuzzy subsets; for example, the classic paper on fuzzy sets by Zadeh [2] discussed the 'set algebra' of fuzzy sets (using sup for union and inf for intersection), and extended the defmition of convexity to fuzzy sets. These and similar ideas allowed many of the methods of image analysis to be generalized to fuzzy image parts. For are cent review on geometric description of fuzzy sets see, e. g. , [3]. Fuzzy methods are also valuable in image processing and coding, where learning processes can be important in choosing the parameters of filters, quantizers, etc. 591 pp. Englisch. Bestandsnummer des Verkäufers 9783790812688
Anzahl: 2 verfügbar
Anbieter: moluna, Greven, Deutschland
Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Application oriented comprehensive volumePractical, timely, effective, comprehensive, understandable and informative, along with an introduction to the subjectAny task that involves decision-making can benefit from soft computing techniques whic. Bestandsnummer des Verkäufers 5310255
Anzahl: Mehr als 20 verfügbar
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Any task that involves decision-making can benefit from soft computing techniques which allow premature decisions to be deferred. The processing and analysis of images is no exception to this rule. In the classical image analysis paradigm, the first step is nearly always some sort of segmentation process in which the image is divided into (hopefully, meaningful) parts. It was pointed out nearly 30 years ago by Prewitt (1] that the decisions involved in image segmentation could be postponed by regarding the image parts as fuzzy, rather than crisp, subsets of the image. It was also realized very early that many basic properties of and operations on image subsets could be extended to fuzzy subsets; for example, the classic paper on fuzzy sets by Zadeh [2] discussed the 'set algebra' of fuzzy sets (using sup for union and inf for intersection), and extended the defmition of convexity to fuzzy sets. These and similar ideas allowed many of the methods of image analysis to be generalized to fuzzy image parts. For are cent review on geometric description of fuzzy sets see, e. g. , [3]. Fuzzy methods are also valuable in image processing and coding, where learning processes can be important in choosing the parameters of filters, quantizers, etc. Bestandsnummer des Verkäufers 9783790812688
Anzahl: 1 verfügbar
Anbieter: California Books, Miami, FL, USA
Zustand: New. Bestandsnummer des Verkäufers I-9783790812688
Anzahl: Mehr als 20 verfügbar