9781848822962 - informationtheory in computer visionand pattern recognition von escolano, francisco; suau, pablo; bonev, boyan (6 Ergebnisse)
InformationTheory in Computer Visionand Pattern Recognition
Escolano Ruiz, Francisco; Suau Pérez, Pablo; Bonev, Boyán Ivanov
- Hardcover
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Information Theory in Computer Vision and Pattern Recognition
Escolano, Francisco/ Suau, Pablo/ Bonev, Boyan/ Yuille, Alan (Foreward By)
- Hardcover
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Hardcover. Zustand: Brand New. 1st edition. 394 pages. 9.75x6.25x1.00 inches. In Stock.
- Hardcover
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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Information theory has proved to be effective for solving many computer visionand pattern recognition (CVPR) problems (such as image matching, clustering and segmentation, saliency detection, feature selection, optimal classifier design and many others). No…wadays, researchers are widely bringing information theory elements to the CVPR arena. Among these elements there are measures (entropy, mutual information.), principles (maximum entropy, minimax entropy.) and theories (rate distortion theory, method of types.).This book explores and introduces the latter elements through an incremental complexity approach at the same time where CVPR problems are formulated and the most representative algorithms are presented. Interesting connections between information theory principles when applied to different problems are highlighted, seeking a comprehensive research roadmap. The result is a novel tool both for CVPR and machine learning researchers, and contributes to across-fertilization of both areas.
Information Theory in Computer Vision and Pattern Recognition
Francisco Escolano Ruiz, Boyán Ivanov Bonev, Pablo Suau Pérez
- Hardcover
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Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 384 | Sprache: Englisch | Produktart: Bücher | Information theory has proved to be effective for solving many computer vision and pattern recognition (CVPR) problems (such as image matching, clustering and segmentation, saliency detection, feature selection, optimal classifier desig…n and many others). Nowadays, researchers are widely bringing information theory elements to the CVPR arena. Among these elements there are measures (entropy, mutual information¿), principles (maximum entropy, minimax entropy¿) and theories (rate distortion theory, method of types¿).This book explores and introduces the latter elements through an incremental complexity approach at the same time where CVPR problems are formulated and the most representative algorithms are presented. Interesting connections between information theory principles when applied to different problems are highlighted, seeking a comprehensive research roadmap. The result is a novel tool both for CVPR and machine learning researchers, and contributes to across-fertilization of both areas.
Information Theory in Computer Vision and Pattern Recognition
Francisco Escolano Ruiz, Boyán Ivanov Bonev, Pablo Suau Pérez
- Hardcover
Anbieter: Buchpark, Trebbin, DeutschlandBuchpark
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EUR 65,87
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Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 384 | Sprache: Englisch | Produktart: Bücher | Information theory has proved to be effective for solving many computer vision and pattern recognition (CVPR) problems (such as image matching, clustering and segmentation, saliency detection, feature selection, optimal classifier desig…n and many others). Nowadays, researchers are widely bringing information theory elements to the CVPR arena. Among these elements there are measures (entropy, mutual information¿), principles (maximum entropy, minimax entropy¿) and theories (rate distortion theory, method of types¿).This book explores and introduces the latter elements through an incremental complexity approach at the same time where CVPR problems are formulated and the most representative algorithms are presented. Interesting connections between information theory principles when applied to different problems are highlighted, seeking a comprehensive research roadmap. The result is a novel tool both for CVPR and machine learning researchers, and contributes to across-fertilization of both areas.
Information Theory in Computer Vision and Pattern Recognition
Francisco Escolano Ruiz, Boyán Ivanov Bonev, Pablo Suau Pérez
- Hardcover
Anbieter: Buchpark, Trebbin, DeutschlandBuchpark
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Gebraucht
EUR 67,85
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Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 384 | Sprache: Englisch | Produktart: Bücher | Information theory has proved to be effective for solving many computer vision and pattern recognition (CVPR) problems (such as image matching, clustering and segmentation, saliency detection, feature selection, optimal classifi…er design and many others). Nowadays, researchers are widely bringing information theory elements to the CVPR arena. Among these elements there are measures (entropy, mutual information¿), principles (maximum entropy, minimax entropy¿) and theories (rate distortion theory, method of types¿).This book explores and introduces the latter elements through an incremental complexity approach at the same time where CVPR problems are formulated and the most representative algorithms are presented. Interesting connections between information theory principles when applied to different problems are highlighted, seeking a comprehensive research roadmap. The result is a novel tool both for CVPR and machine learning researchers, and contributes to across-fertilization of both areas.
