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Titolo: |
Energy Minimization Methods in Computer Vision and Pattern Recognition [[electronic resource] ] : 11th International Conference, EMMCVPR 2017, Venice, Italy, October 30 – November 1, 2017, Revised Selected Papers / / edited by Marcello Pelillo, Edwin Hancock
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Pubblicazione: | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
Edizione: | 1st ed. 2018. |
Descrizione fisica: | 1 online resource (XII, 582 p.) |
Disciplina: | 006.37 |
Soggetto topico: | Pattern recognition |
Arithmetic and logic units, Computer | |
Optical data processing | |
Numerical analysis | |
Computer science—Mathematics | |
Artificial intelligence | |
Pattern Recognition | |
Arithmetic and Logic Structures | |
Image Processing and Computer Vision | |
Numeric Computing | |
Math Applications in Computer Science | |
Artificial Intelligence | |
Persona (resp. second.): | PelilloMarcello |
HancockEdwin | |
Nota di bibliografia: | Includes bibliographical references and index. |
Nota di contenuto: | Clustering and Quantum Methods -- Motion and Tracking -- Image Processing and Segmentation -- Color, Shading and Reflectance of Light -- Propagation and Time-evolution -- Inference, Labeling, and Relaxation. |
Sommario/riassunto: | This volume constitutes the refereed proceedings of the 11th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2017, held in Venice, Italy, in October/November 2017. The 37 revised full papers were carefully reviewed and selected from 51 submissions. The papers are organized in topical sections on Clustering and Quantum Methods; Motion and Tracking; Image Processing and Segmentation; Color, Shading and Reflectance of Light; Propagation and Time-evolution; and Inference, Labeling, and Relaxation. |
Titolo autorizzato: | Energy Minimization Methods in Computer Vision and Pattern Recognition ![]() |
ISBN: | 3-319-78199-5 |
Formato: | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 996465518603316 |
Lo trovi qui: | Univ. di Salerno |
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