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ISBN 10: 0750322454 ISBN 13: 9780750322454
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Published by Institute of Physics Publishing, 2022
ISBN 10: 0750322454 ISBN 13: 9780750322454
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Published by Institute of Physics Publishing 12/20/2022, 2022
ISBN 10: 0750322454 ISBN 13: 9780750322454
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Paperback or Softback. Condition: New. Multimodality Imaging, Volume 1: Deep learning applications. Book.
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Published by Institute of Physics Publishing, 2022
ISBN 10: 0750322454 ISBN 13: 9780750322454
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Published by Institute of Physics Publishing, 2022
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Published by Institute of Physics Publishing, 2022
ISBN 10: 0750322454 ISBN 13: 9780750322454
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Published by IOP Publishing Ltd Dez 2022, 2022
ISBN 10: 0750322454 ISBN 13: 9780750322454
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Taschenbuch. Condition: Neu. Neuware - This research and reference text explores the finer details of Deep Learning models. It provides a brief outline on popular models including convolution neural networks (CNN), deep belief networks (DBN), autoencoders, residual neural networks (Res Nets). The text discusses some of the Deep Learning-based applications in gene identification. Sections in the book explore the foundation and necessity of deep learning in radiology, the application of deep learning in the area of cardiovascular imaging and deep learning applications in the area of fatty liver disease characterization and COVID19, respectively.
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Published by Institute of Physics Publishing, 2021
ISBN 10: 075032242X ISBN 13: 9780750322423
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Published by IOP Publishing Ltd Dez 2022, 2022
ISBN 10: 075032242X ISBN 13: 9780750322423
Seller: AHA-BUCH GmbH, Einbeck, Germany
Buch. Condition: Neu. Neuware - This research and reference text explores the finer details of Deep Learning models. It provides a brief outline on popular models including convolution neural networks (CNN), deep belief networks (DBN), autoencoders, residual neural networks (Res Nets). The text discusses some of the Deep Learning-based applications in gene identification. Sections in the book explore the foundation and necessity of deep learning in radiology, the application of deep learning in the area of cardiovascular imaging and deep learning applications in the area of fatty liver disease characterization and COVID19, respectively.