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Efficient Algorithms for Global Optimization Methods in Computer Vision: International Dagstuhl Seminar, Dagstuhl Castle, Germany, November 20-25, 2011, Revised Selected Papers: 8293 - Brossura
This book constitutes the thoroughly refereed post-conference proceedings of the International Dagstuhl-Seminar on Efficient Algorithms for Global Optimization Methods in Computer Vision, held in Dagstuhl Castle, Germany, in November 2011. The 8 revised full papers presented were carefully reviewed and selected by 12 lectures given at the seminar. The seminar focused on the entire algorithmic development pipeline for global optimization problems in computer vision: modelling, mathematical analysis, numerical solvers and parallelization. In particular, the goal of the seminar was to bring together researchers from all four fields to analyze and discuss the connections between the different stages of the algorithmic design pipeline.
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Contenuti:
Mathematical Optimization.- Modeling.- Nonconvex Optimization.- Shape Representations.
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- EditoreSpringer
- Data di pubblicazione2014
- ISBN 10 3642547737
- ISBN 13 9783642547737
- RilegaturaCopertina flessibile
- Numero di pagine184
- RedattoreBruhn Andrés, Pock Thomas, Tai Xue-Cheng
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Efficient Algorithms for Global Optimization Methods in Computer Vision
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ISBN 10: 3642547737
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Descrizione libro Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book constitutes the thoroughly refereed post-conference proceedings of the International Dagstuhl-Seminar on Efficient Algorithms for Global Optimization Methods in Computer Vision, held in Dagstuhl Castle, Germany, in November 2011. The 8 revised full papers presented were carefully reviewed and selected by 12 lectures given at the seminar. The seminar focused on the entire algorithmic development pipeline for global optimization problems in computer vision: modelling, mathematical analysis, numerical solvers and parallelization. In particular, the goal of the seminar was to bring together researchers from all four fields to analyze and discuss the connections between the different stages of the algorithmic design pipeline. 184 pp. Englisch. Codice articolo 9783642547737
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Efficient Algorithms for Global Optimization Methods in Computer Vision: International Dagstuhl Seminar, Dagstuhl Castle, Germany, November 20-25, 2011, Revised Selected Papers
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Descrizione libro Paperback. Condizione: Brand New. 2014 edition. 190 pages. 9.10x6.00x0.50 inches. In Stock. Codice articolo x-3642547737
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Descrizione libro Condizione: New. Editor(s): Pock, Thomas; Tai, Xue-Cheng; Bruhn, Andres. Series: Lecture Notes in Computer Science / Image Processing, Computer Vision, Pattern Recognition, and Graphics. Num Pages: 182 pages, 128 black & white illustrations, biography. BIC Classification: UMB; UYA; UYT. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 10. Weight in Grams: 290. . 2014. Paperback. . . . . Codice articolo V9783642547737
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Efficient Algorithms for Global Optimization Methods in Computer Vision : International Dagstuhl Seminar, Dagstuhl Castle, Germany, November 20-25, 2011, Revised Selected Papers
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(2014)
ISBN 10: 3642547737
ISBN 13: 9783642547737
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Descrizione libro Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the thoroughly refereed post-conference proceedings of the International Dagstuhl-Seminar on Efficient Algorithms for Global Optimization Methods in Computer Vision, held in Dagstuhl Castle, Germany, in November 2011. The 8 revised full papers presented were carefully reviewed and selected by 12 lectures given at the seminar. The seminar focused on the entire algorithmic development pipeline for global optimization problems in computer vision: modelling, mathematical analysis, numerical solvers and parallelization. In particular, the goal of the seminar was to bring together researchers from all four fields to analyze and discuss the connections between the different stages of the algorithmic design pipeline. Codice articolo 9783642547737
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