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ISBN 10: 0128097035 ISBN 13: 9780128097038
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Publicado por Elsevier Science Publishing Co Inc, 2016
ISBN 10: 0128097035 ISBN 13: 9780128097038
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Publicado por Elsevier Science Publishing Co Inc, US, 2016
ISBN 10: 0128097035 ISBN 13: 9780128097038
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Añadir al carritoPaperback. Condición: New. Example-Based Super Resolution provides a thorough introduction and overview of example-based super resolution, covering the most successful algorithmic approaches and theories behind them with implementation insights. It also describes current challenges and explores future trends. Readers of this book will be able to understand the latest natural image patch statistical models and the performance limits of example-based super resolution algorithms, select the best state-of-the-art algorithmic alternative and tune it for specific use cases, and quickly put into practice implementations of the latest and most successful example-based super-resolution methods.
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Idioma: Inglés
Publicado por Academic Press 2016-09, 2016
ISBN 10: 0128097035 ISBN 13: 9780128097038
Librería: Chiron Media, Wallingford, Reino Unido
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Añadir al carritoKartoniert / Broschiert. Condición: New. Provides detailed coverage of techniques and implementation details that have been successfully introduced in diverse and demanding real-world applications Covers a wide variety of machine learning approaches, ranging from cross-scale self.
Idioma: Inglés
Publicado por Elsevier Science Publishing Co Inc, US, 2016
ISBN 10: 0128097035 ISBN 13: 9780128097038
Librería: Rarewaves.com UK, London, Reino Unido
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Añadir al carritoPaperback. Condición: New. Example-Based Super Resolution provides a thorough introduction and overview of example-based super resolution, covering the most successful algorithmic approaches and theories behind them with implementation insights. It also describes current challenges and explores future trends. Readers of this book will be able to understand the latest natural image patch statistical models and the performance limits of example-based super resolution algorithms, select the best state-of-the-art algorithmic alternative and tune it for specific use cases, and quickly put into practice implementations of the latest and most successful example-based super-resolution methods.
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Añadir al carritoTaschenbuch. Condición: Neu. Example-Based Super Resolution | Jordi Salvador | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2016 | Academic Press | EAN 9780128097038 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Idioma: Inglés
Publicado por Elsevier Science Publishing Co Inc, 2016
ISBN 10: 0128097035 ISBN 13: 9780128097038
Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Example-Based Super Resolution provides a thorough introduction and overview of example-based super resolution, covering the most successful algorithmic approaches and theories behind them with implementation insights. It also describes current challenges and explores future trends. Readers of this book will be able to understand the latest natural image patch statistical models and the performance limits of example-based super resolution algorithms, select the best state-of-the-art algorithmic alternative and tune it for specific use cases, and quickly put into practice implementations of the latest and most successful example-based super-resolution methods. Englisch.
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Example-Based Super Resolution provides a thorough introduction and overview of example-based super resolution, covering the most successful algorithmic approaches and theories behind them with implementation insights. It also describes current challenges and explores future trends. Readers of this book will be able to understand the latest natural image patch statistical models and the performance limits of example-based super resolution algorithms, select the best state-of-the-art algorithmic alternative and tune it for specific use cases, and quickly put into practice implementations of the latest and most successful example-based super-resolution methods.