Deep Learning Data Labeling (15 results)
Deep Learning and Data Labeling for Medical Applications : First International Workshop, LABELS 2016, and Second International Workshop, DLMIA 2016 Held in Conjunction with MICCAI 2016, Athens, Greece, October 21, 2016 Proceedings
Carneiro, Gustavo (EDT); Mateus, Diana (EDT); Loïc, Peter (EDT); Bradley, Andrew (EDT); Tavares, João Manuel R. S. (EDT)
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Deep Learning and Data Labeling for Medical Applications : First International Workshop, LABELS 2016, and Second International Workshop, DLMIA 2016 Held in Conjunction with MICCAI 2016, Athens, Greece, October 21, 2016 Proceedings
Carneiro, Gustavo (EDT); Mateus, Diana (EDT); Loïc, Peter (EDT); Bradley, Andrew (EDT); Tavares, João Manuel R. S. (EDT)
- Softcover
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Deep Learning and Data Labeling for Medical Applications : First International Workshop, LABELS 2016, and Second International Workshop, DLMIA 2016 Held in Conjunction with MICCAI 2016, Athens, Greece, October 21, 2016 Proceedings
Carneiro, Gustavo (EDT); Mateus, Diana (EDT); Loïc, Peter (EDT); Bradley, Andrew (EDT); Tavares, João Manuel R. S. (EDT)
- Softcover
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Condition: New. pp. 293 1st ed. 2016 edition NO-PA16APR2015-KAP.
Deep Learning and Data Labeling for Medical Applications : First International Workshop, LABELS 2016, and Second International Workshop, DLMIA 2016 Held in Conjunction with MICCAI 2016, Athens, Greece, October 21, 2016 Proceedings
Carneiro, Gustavo (EDT); Mateus, Diana (EDT); Loïc, Peter (EDT); Bradley, Andrew (EDT); Tavares, João Manuel R. S. (EDT)
- Softcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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Paperback. Condition: Brand New. 277 pages. 9.00x6.00x0.75 inches. In Stock.
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Taschenbuch. Condition: 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-Sc…ale 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.
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Taschenbuch. Condition: Neu. Deep Learning and Data Labeling for Medical Applications | First International Workshop, LABELS 2016, and Second International Workshop, DLMIA 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 21, 2016, Proceedings | Gustavo Carneiro (u. a.) | Taschenbuch | Lecture Notes in Computer… Science | xiii | Englisch | 2016 | Springer | EAN 9783319469751 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Condition: new. Questo è un articolo print on demand.
Language: English
Published by Springer International Publishing Sep 2016 2016
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 Work…shop 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. 296 pp. Englisch.
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Seller: Majestic Books, Hounslow, , United KingdomMajestic Books
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Condition: New. Print on Demand pp. 293.
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Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios
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Condition: New. PRINT ON DEMAND pp. 293.
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Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 Annot.
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Active learning.- Semi-supervised learning.- Reinforcement learning.- Domain adaptation and transfer learning.- Crowd-sourcing annotations and fusion of labels from different sources.- Data augmentation.- Modelling of label uncertainty.…- Visualization and human-computer interaction.- 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.- Applications based on deep learning techniques.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 296 pp. Englisch.
