R mateus (114 resultados)

Condición: New. Manhanini, Mateus (ilustrador).

Condición: As New. Unread book in perfect condition. Manhanini, Mateus (ilustrador).

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Condición: As New. Unread book in perfect condition.

Paperback. Condición: Brand New. 363 pages. 8.00x5.00x0.91 inches. In Stock.

Condición: New. Santolouco, Mateus; Wachter, Dave (ilustrador).

Paperback. Condición: Good. This book constitutes the refereed proceedings of two workshops held at the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICAI 2016, in Athens, Greece, in October 2016: the First Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2016, and the Second International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2016. The 28 revised regular papers presented in this book were carefully reviewed and selected from a total of 52 submissions. The 7 papers selected for LABELS deal with topics from the following fields: crowd-sourcing methods; active learning; transfer learning; semi-supervised learning; and modeling of label uncertainty.The 21 papers selected for DLMIA span a wide range of topics such as image description; medical imaging-based diagnosis; medical signal-based diagnosis; medical image reconstruction and model selection using deep learning techniques; meta-heuristic techniques for fine-tuning parameter in deep learning-based architectures; and applications based on deep learning techniques.…

Condición: New. Santolouco, Mateus; Smith, Cory; Schoening, Dan (ilustrador).

Paperback. Condición: Good. This book constitutes the refereed proceedings of two workshops held at the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICAI 2016, in Athens, Greece, in October 2016: the First Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2016, and the Second International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2016. The 28 revised regular papers presented in this book were carefully reviewed and selected from a total of 52 submissions. The 7 papers selected for LABELS deal with topics from the following fields: crowd-sourcing methods; active learning; transfer learning; semi-supervised learning; and modeling of label uncertainty.The 21 papers selected for DLMIA span a wide range of topics such as image description; medical imaging-based diagnosis; medical signal-based diagnosis; medical image reconstruction and model selection using deep learning techniques; meta-heuristic techniques for fine-tuning parameter in deep learning-based architectures; and applications based on deep learning techniques.…

Condición: As New. Unread book in perfect condition. Santolouco, Mateus; Wachter, Dave (ilustrador).

Condición: As New. Unread book in perfect condition. Santolouco, Mateus; Smith, Cory; Schoening, Dan (ilustrador).

Condición: New.

Paperback. Condición: New. Brand new book, sourced directly from publisher. Dispatch time is 24-48 hours from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Condición: New. Santolouco, Mateus; Smith, Cory; Schoening, Dan (ilustrador).

Condición: As New. Unread book in perfect condition.

Condición: New.

Condición: New. Santolouco, Mateus; Wachter, Dave (ilustrador).

Condición: As New. Unread book in perfect condition. Santolouco, Mateus; Smith, Cory; Schoening, Dan (ilustrador).

Condición: As New. Unread book in perfect condition. Santolouco, Mateus; Wachter, Dave (ilustrador).

Condición: New.

Condición: New.

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Kartoniert / Broschiert. Condición: New.

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Condición: leido. Ariel grandes batallas. 1ª ed., 1ª imp. edición. cartoné. 432.

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Condición: New. pp. 293 1st ed. 2016 edition NO-PA16APR2015-KAP.

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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed proceedings of two workshops held at the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, in Athens, Greece, in October 2016: the First Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2016, and the Second International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2016. The 28 revised regular papers presented in this book were carefully reviewed and selected from a total of 52 submissions. The 7 papers selected for LABELS deal with topics from the following fields: crowd-sourcing methods;active learning;transfer learning;semi-supervised learning; and modeling of label uncertainty.The 21 papers selected for DLMIA span a wide range of topics such as image description; medical imaging-based diagnosis; medical signal-based diagnosis; medical image reconstruction and model selection using deep learning techniques; meta-heuristic techniques for fine-tuning parameter in deep learning-based architectures; and applications based on deep learning techniques. …