Xi xiaohuan (41 Ergebnisse)

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Zustand: New. Cheng Wang is a Professor at the Aerospace Information Research Institute, Chinese Academy of Sciences (CAS), Beijing, China. He earned a PhD in remote sensing at the University of Strasbourg, France, in 2005. He presently serves as Dire.

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Zustand: New. pp. 504 1st ed. 2024 edition NO-PA16APR2015-KAP.

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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The two-volume set LNCS 14348 and 14139 constitutes the proceedings of the 14th International Workshop on Machine Learning in Medical Imaging, MLMI 2023, held in conjunction with MICCAI 2023, in Vancouver, Canada, in October 2023. The 93 full papers presented in the proceedings were carefully reviewed and selected from 139 submissions. They focus onmajor trends and challenges in artificial intelligence and machine learning in the medical imaging field, translating medical imaging research into clinical practice. Topics of interests included deep learning, generative adversarial learning, ensemble learning, transfer learning, multi-task learning, manifold learning, reinforcement learning, along with their applications to medical image analysis, computer-aided diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc.…

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The two-volume set LNCS 14348 and 14139 constitutes the proceedings of the 14th International Workshop on Machine Learning in Medical Imaging, MLMI 2023, held in conjunction with MICCAI 2023, in Vancouver, Canada, in October 2023. The 93 full papers presented in the proceedings were carefully reviewed and selected from 139 submissions. They focus onmajor trends and challenges in artificial intelligence and machine learning in the medical imaging field, translating medical imaging research into clinical practice. Topics of interests included deep learning, generative adversarial learning, ensemble learning, transfer learning, multi-task learning, manifold learning, reinforcement learning, along with their applications to medical image analysis, computer-aided diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc.…

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Paperback. Zustand: Brand New. 502 pages. 9.26x6.10x1.01 inches. In Stock.

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Taschenbuch. Zustand: Neu. Machine Learning in Medical Imaging | 14th International Workshop, MLMI 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings, Part II | Xiaohuan Cao (u. a.) | Taschenbuch | Lecture Notes in Computer Science | xxi | Englisch | 2023 | Springer | EAN 9783031456756 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Taschenbuch. Zustand: Neu. Machine Learning in Medical Imaging | 14th International Workshop, MLMI 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings, Part I | Xiaohuan Cao (u. a.) | Taschenbuch | Lecture Notes in Computer Science | xxii | Englisch | 2023 | Springer | EAN 9783031456725 | 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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Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 504 | Sprache: Englisch | Produktart: Bücher | The two-volume set LNCS 14348 and 14139 constitutes the proceedings of the 14th International Workshop on Machine Learning in Medical Imaging, MLMI 2023, held in conjunction with MICCAI 2023, in Vancouver, Canada, in October 2023. The 93 full papers presented in the proceedings were carefully reviewed and selected from 139 submissions. They focus on major trends and challenges in artificial intelligence and machine learning in the medical imaging field, translating medical imaging research into clinical practice. Topics of interests included deep learning, generative adversarial learning, ensemble learning, transfer learning, multi-task learning, manifold learning, reinforcement learning, along with their applications to medical image analysis, computer-aided diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc.…

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