Heng Huang - Böcker
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4 produkter
4 produkter
115 kr
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Del 11846 - Lecture Notes in Computer Science
Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy
4th International Workshop, MBIA 2019, and 7th International Workshop, MFCA 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings
Häftad, Engelska, 2019
556 kr
Skickas inom 10-15 vardagar
This book constitutes the refereed joint proceedings of the 4th International Workshop on Multimodal Brain Image Analysis, MBAI 2019, and the 7th International Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2019, held in conjunction with the 22nd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2019, in Shenzhen, China, in October 2019.The 16 full papers presented at MBAI 2019 and the 7 full papers presented at MFCA 2019 were carefully reviewed and selected.The MBAI papers intend to move forward the state of the art in multimodal brain image analysis, in terms of analysis methodologies, algorithms, software systems, validation approaches, benchmark datasets, neuroscience, and clinical applications.The MFCA papers are devoted to statistical and geometrical methods for modeling the variability of biological shapes. The goal is to foster the interactions between the mathematical community around shapes and the MICCAI community around computational anatomy applications.
Del 8159 - Lecture Notes in Computer Science
Multimodal Brain Image Analysis
Third International Workshop, MBIA 2013, Held in Conjunction with MICCAI 2013, Nagoya, Japan, September 22, 2013, Proceedings
Häftad, Engelska, 2013
551 kr
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This book constitutes the refereed proceedings of the Third International Workshop on Multimodal Brain Image Analysis, MBIA 2013, held in Nagoya, Japan, on September 22, 2013 in conjunction with the 16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI.
2 244 kr
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Authored by researchers and practitioners who build cutting-edge federated learning applications to solve real-world problems, this book covers the spectrum of federated learning technology from concepts and application scenarios to advanced algorithms and finally system implementation in three parts. It provides a comprehensive review and summary of federated learning technology, as well as presenting numerous novel federated learning algorithms which no other books have summarized. The work also references the most recent papers, articles and reviews from the past several years to keep pace with the academic and industrial state of the art of federated learning.The first part lays a foundational understanding of federated learning by going through its definition and characteristics, and also possible application scenarios and related privacy protection technologies. The second part elaborates on some of the federated learning algorithms innovated by JD Technology which encompass both vertical and horizontal scenarios, including vertical federated tree models, linear regression, kernel learning, asynchronous methods, deep learning, homomorphic encryption, and reinforcement learning. The third and final part shifts in scope to federated learning systems — namely JD Technology's own FedLearn system — by discussing its design and implementation using gRPC, in addition to specific performance optimization techniques plus integration with blockchain technology.This book will serve as a great reference for readers who are experienced in federated learning algorithms, building privacy-preserving machine learning applications or solving real-world problems with privacy-restricted scenarios.