Chunfeng cui (28 résultats)

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Etat : New. In English.

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Etat : New. 1st ed. 2022 edition NO-PA16APR2015-KAP.

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the proceedings of the 13th International Workshop on Machine Learning in Medical Imaging, MLMI 2022, held in conjunction with MICCAI 2022, in Singapore, in September 2022. The 48 full papers presented in this volume were carefully reviewed and selected from 64 submissions. They focus on major trends and challenges in the above-mentioned area, aiming to identify new-cutting-edge techniques and their uses in medical imaging. Topics dealt with are: deep learning, generative adversarial learning, ensemble learning, sparse learning, multi-task learning, multi-view learning, manifold learning, and reinforcement learning, with their applications to medical image analysis, computer-aided detection and diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc.…

Paperback. Etat : Brand New. 492 pages. 9.25x6.10x1.18 inches. In Stock.

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Taschenbuch. Etat : Neu. Machine Learning in Medical Imaging | 13th International Workshop, MLMI 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings | Chunfeng Lian (u. a.) | Taschenbuch | Lecture Notes in Computer Science | xiii | Englisch | 2022 | Springer | EAN 9783031210136 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Etat : Hervorragend. Zustand: Hervorragend | Seiten: 496 | Sprache: Englisch | Produktart: Bücher | This book constitutes the proceedings of the 13th International Workshop on Machine Learning in Medical Imaging, MLMI 2022, held in conjunction with MICCAI 2022, in Singapore, in September 2022. The 48 full papers presented in this volume were carefully reviewed and selected from 64 submissions. They focus on major trends and challenges in the above-mentioned area, aiming to identify new-cutting-edge techniques and their uses in medical imaging. Topics dealt with are: deep learning, generative adversarial learning, ensemble learning, sparse learning, multi-task learning, multi-view learning, manifold learning, and reinforcement learning, with their applications to medical image analysis, computer-aided detection and diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc.…

Etat : New. 1st edition NO-PA16APR2015-KAP.

Etat : New.

Etat : New.

Etat : New.

Etat : New.

Etat : As New. Unread book in perfect condition.

Etat : As New. Unread book in perfect condition.

Etat : New. Provides a timely (given the 6G specifications and standards that begin in 2025) and systematic overview of key enabling technologies for the 6G air interfaceIncludes a discussion of potential future developments that takes account of the b.

Paperback. Etat : Brand New. 500 pages. 9.00x6.00x1.34 inches. In Stock.

Taschenbuch. Etat : Neu. Neuware - Key Technologies for the 6G Air Interface is an up-to-date reference, providing comprehensive, systematic, and in-depth descriptions of the enabling technologies for the 6G air interface. It includes recent advances, potential future developments, and associated specifications and standards.Simulations and quantitative analyses are used to provide a comprehensive understanding of the performance potential of candidate technologies and their implementation impacts.Recent breakthroughs in fields such as information theory and multi-antenna technology are explained which enables readers to grasp the potential major technology revolution expected for the 6G air interface. Researchers working toward the 6G time frame, industry analysts, governments, and investors monitoring the migration of the mobile industry from 5G to 6G will gain insights from the discussions of the rapid technological developments that are expected, the challenges, the potential for future applications and opportunities, and the balance of innovation and feasibility.…

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PF. Etat : New. This item is printed on demand. Brand new book, sourced directly from publisher. Dispatch time is 6-7 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book constitutes the proceedings of the 13th International Workshop on Machine Learning in Medical Imaging, MLMI 2022, held in conjunction with MICCAI 2022, in Singapore, in September 2022. The 48 full papers presented in this volume were carefully reviewed and selected from 64 submissions. They focus on major trends and challenges in the above-mentioned area, aiming to identify new-cutting-edge techniques and their uses in medical imaging. Topics dealt with are: deep learning, generative adversarial learning, ensemble learning, sparse learning, multi-task learning, multi-view learning, manifold learning, and reinforcement learning, with their applications to medical image analysis, computer-aided detection and diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc. 496 pp. Englisch.…

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book constitutes the proceedings of the 13th International Workshop on Machine Learning in Medical Imaging, MLMI 2022, held in conjunction with MICCAI 2022, in Singapore, in September 2022. The 48 full papers presented in this volume were carefully.…

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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book constitutes the proceedings of the 13th International Workshop on Machine Learning in Medical Imaging, MLMI 2022, held in conjunction with MICCAI 2022, in Singapore, in September 2022.The 48 full papers presented in this volume were carefully reviewed and selected from 64 submissions. They focus on major trends and challenges in the above-mentioned area, aiming to identify new-cutting-edge techniques and their uses in medical imaging. Topics dealt with are: deep learning, generative adversarial learning, ensemble learning, sparse learning, multi-task learning, multi-view learning, manifold learning, and reinforcement learning, with their applications to medical image analysis, computer-aided detection and diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 496 pp. Englisch.…

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