Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning

Second MICCAI Workshop, DART 2020, and First MICCAI Workshop, DCL 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4–8, 2020, Proceedings

Häftad, Engelska, 2020

Av Shadi Albarqouni, Spyridon Bakas, Konstantinos Kamnitsas, M. Jorge Cardoso, Bennett Landman, Wenqi Li, Fausto Milletari, Nicola Rieke, Holger Roth, Daguang Xu, Ziyue Xu

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This book constitutes the refereed proceedings of the Second MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2020, and the First MICCAI Workshop on Distributed and Collaborative Learning, DCL 2020, held in conjunction with MICCAI 2020 in October 2020.

Produktinformation

Utgivningsdatum2020-09-26
Mått155 x 235 x 13 mm
Vikt353 g
FormatHäftad
SpråkEngelska
SerieLecture Notes in Computer Science
Antal sidor212
FörlagSpringer Nature Switzerland AG
ISBN9783030605476

Tillhör följande kategorier

a-Unet++:A Data-driven Neural Network Architecture for Medical Image Segmentation.- DAPR-Net: Domain Adaptive Predicting-refinement Network for Retinal Vessel Segmentation.- Augmented Radiology: Patient-wise Feature Transfer Model for Glioma Grading.- Attention-Guided Deep Domain Adaptation for Brain Dementia Identication with Multi-Site Neuroimaging Data.- Registration of Histopathology Images Using Self Supervised Fine Grained Feature Maps.- Cross-Modality Segmentation by Self-Supervised Semantic Alignment in Disentangled Content Space.- Semi-supervised Pathology Segmentation with Disentangled Representations.- Domain Generalizer: A Few-shot Meta Learning Framework for Domain Generalization in Medical Imaging.- Parts2Whole: Self-supervised Contrastive Learning via Reconstruction.- Cross-View Label Transfer in Knee MR Segmentation Using Iterative Context Learning.- Continual Class Incremental Learning for CT Thoracic Segmentation.- First U-Net Layers Contain More Domain SpecificInformation Than The Last Ones.- Siloed Federated Learning for Multi-Centric Histopathology Datasets.- On the Fairness of Privacy-Preserving Representations in Medical Applications.- Inverse Distance Aggregation for Federated Learning with Non-IID Data.- Weight Erosion: an Update Aggregation Scheme for Personalized Collaborative Machine Learning.- Federated Gradient Averaging for Multi-Site Training with Momentum-Based Optimizers.- Federated Learning for Breast Density Classification: A Real-World Implementation.- Automated Pancreas Segmentation Using Multi-institutional Collaborative Deep Learning.- Fed-BioMed: A general open-source frontend framework for federated learning in healthcare.

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