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Machine Learning in Medical Imaging : 11th International Workshop, Mlmi 2020,...

Description: Machine Learning in Medical Imaging : 11th International Workshop, Mlmi 2020, Held in Conjunction With Miccai 2020, Lima, Peru, October 4, 2020, Proceedings, Paperback by Liu, Mingxia (EDT); Yan, Pingkun (EDT); Lian, Chunfeng (EDT); Cao, Xiaohuan (EDT), ISBN 3030598608, ISBN-13 9783030598600, Brand New, Free shipping in the US This book constitutes the proceedings of the 11th International Workshop on Machine Learning in Medical Imaging, MLMI 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020. The conference was held virtually due to the COVID-19 pandemic. The 68 papers presented in this volume were carefully reviewed and selected from 101 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, pathology, etc.

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End Time: 2024-12-29T11:02:03.000Z

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Machine Learning in Medical Imaging : 11th International Workshop, Mlmi 2020,...

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Book Title: Machine Learning in Medical Imaging : 11th International Workshop

Number of Pages: Xv, 686 Pages

Publication Name: Machine Learning in Medical Imaging : 11th International Workshop, MLMI 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Proceedings

Language: English

Publisher: Springer International Publishing A&G

Subject: Intelligence (Ai) & Semantics, Enterprise Applications / General, Computer Vision & Pattern Recognition

Publication Year: 2020

Type: Textbook

Item Weight: 37.5 Oz

Subject Area: Computers

Author: Pingkun Yan

Item Length: 9.3 in

Item Width: 6.1 in

Series: Lecture Notes in Computer Science Ser.

Format: Trade Paperback

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