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Añadir al carritoCondición: New. pp. 124 23:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on White w/Gloss Lam.
Idioma: Inglés
Publicado por Morgan Kaufmann 2013-07-15, 2013
ISBN 10: 0124077412 ISBN 13: 9780124077416
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Publicado por Elsevier Science and Technology, US, 2013
ISBN 10: 0124077412 ISBN 13: 9780124077416
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
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Añadir al carritoPaperback. Condición: New. High Performance Deformable Image Registration Algorithms for Manycore Processors develops highly data-parallel image registration algorithms suitable for use on modern multi-core architectures, including graphics processing units (GPUs). Focusing on deformable registration, we show how to develop data-parallel versions of the registration algorithm suitable for execution on the GPU. Image registration is the process of aligning two or more images into a common coordinate frame and is a fundamental step to be able to compare or fuse data obtained from different sensor measurements. Extracting useful information from 2D/3D data is essential to realizing key technologies underlying our daily lives. Examples include autonomous vehicles and humanoid robots that can recognize and manipulate objects in cluttered environments using stereo vision and laser sensing and medical imaging to localize and diagnose tumors in internal organs using data captured by CT/MRI scans.
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Publicado por Elsevier Science & Technology, 2013
ISBN 10: 0124077412 ISBN 13: 9780124077416
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Publicado por Morgan Kaufmann Publishers Inc. 2013-07, 2013
ISBN 10: 0124077412 ISBN 13: 9780124077416
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Añadir al carritoKartoniert / Broschiert. Condición: New. Demonstrates how to redesign widely used image registration algorithms so as to best expose the underlying parallelism available in these algorithms Shows how to pose and implement the parallel versions of the algorithms within the single .
Idioma: Inglés
Publicado por Elsevier Science and Technology, US, 2013
ISBN 10: 0124077412 ISBN 13: 9780124077416
Librería: Rarewaves.com UK, London, Reino Unido
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Añadir al carritoPaperback. Condición: New. High Performance Deformable Image Registration Algorithms for Manycore Processors develops highly data-parallel image registration algorithms suitable for use on modern multi-core architectures, including graphics processing units (GPUs). Focusing on deformable registration, we show how to develop data-parallel versions of the registration algorithm suitable for execution on the GPU. Image registration is the process of aligning two or more images into a common coordinate frame and is a fundamental step to be able to compare or fuse data obtained from different sensor measurements. Extracting useful information from 2D/3D data is essential to realizing key technologies underlying our daily lives. Examples include autonomous vehicles and humanoid robots that can recognize and manipulate objects in cluttered environments using stereo vision and laser sensing and medical imaging to localize and diagnose tumors in internal organs using data captured by CT/MRI scans.
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Añadir al carritoTaschenbuch. Condición: Neu. High Performance Deformable Image Registration Algorithms for Manycore Processors | James Shackleford (u. a.) | Taschenbuch | Einband - fest (Hardcover) | Englisch | 2013 | Morgan Kaufmann | EAN 9780124077416 | Verantwortliche Person für die EU: Zeitfracht Medien GmbH, Ferdinand-Jühlke-Str. 7, 99095 Erfurt, produktsicherheit[at]zeitfracht[dot]de | Anbieter: preigu.
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Añadir al carritoPaperback. Condición: Brand New. 114 pages. 9.00x6.25x0.50 inches. In Stock. This item is printed on demand.
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Publicado por Elsevier Science & Technology, 2013
ISBN 10: 0124077412 ISBN 13: 9780124077416
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Añadir al carritoPaperback / softback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
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Publicado por Elsevier Science & Technology, Morgan Kaufmann, 2013
ISBN 10: 0124077412 ISBN 13: 9780124077416
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - High Performance Deformable Image Registration Algorithms for Manycore Processors develops highly data-parallel image registration algorithms suitable for use on modern multi-core architectures, including graphics processing units (GPUs). Focusing on deformable registration, we show how to develop data-parallel versions of the registration algorithm suitable for execution on the GPU. Image registration is the process of aligning two or more images into a common coordinate frame and is a fundamental step to be able to compare or fuse data obtained from different sensor measurements. Extracting useful information from 2D/3D data is essential to realizing key technologies underlying our daily lives. Examples include autonomous vehicles and humanoid robots that can recognize and manipulate objects in cluttered environments using stereo vision and laser sensing and medical imaging to localize and diagnose tumors in internal organs using data captured by CT/MRI scans.
Idioma: Inglés
Publicado por Elsevier Science & Technology, Morgan Kaufmann, 2013
ISBN 10: 0124077412 ISBN 13: 9780124077416
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 150,00
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -High Performance Deformable Image Registration Algorithms for Manycore Processors develops highly data-parallel image registration algorithms suitable for use on modern multi-core architectures, including graphics processing units (GPUs). Focusing on deformable registration, we show how to develop data-parallel versions of the registration algorithm suitable for execution on the GPU. Image registration is the process of aligning two or more images into a common coordinate frame and is a fundamental step to be able to compare or fuse data obtained from different sensor measurements. Extracting useful information from 2D/3D data is essential to realizing key technologies underlying our daily lives. Examples include autonomous vehicles and humanoid robots that can recognize and manipulate objects in cluttered environments using stereo vision and laser sensing and medical imaging to localize and diagnose tumors in internal organs using data captured by CT/MRI scans. Englisch.