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Produktbild: Distributed, Collaborative, and Federated Learning, and Affordable AI and Healthcare for Resource Diverse Global Health
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Distributed, Collaborative, and Federated Learning, and Affordable AI and Healthcare for Resource Diverse Global Health Third MICCAI Workshop, DeCaF 2022, and Second MICCAI Workshop, FAIR 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18 and 22, 2022, Proceedings

Aus der Reihe Lecture Notes in Computer Science

49,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

09.10.2022

Herausgeber

M. Jorge Cardoso + weitere

Verlag

Springer

Seitenzahl

204

Maße (L/B/H)

23,5/15,5/1,3 cm

Gewicht

341 g

Auflage

1st ed. 2022

Sprache

Englisch

ISBN

978-3-031-18522-9

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

09.10.2022

Herausgeber

Verlag

Springer

Seitenzahl

204

Maße (L/B/H)

23,5/15,5/1,3 cm

Gewicht

341 g

Auflage

1st ed. 2022

Sprache

Englisch

ISBN

978-3-031-18522-9

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

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  • Produktbild: Distributed, Collaborative, and Federated Learning, and Affordable AI and Healthcare for Resource Diverse Global Health
  • Distributed, Collaborative, and Federated Learning.- Incremental Learning Meets Transfer Learning: Application to Multi-site Prostate MRI Segmentation .- FedAP: Adaptive Personalization in Federated Learning for Non-IID Data Data Stealing Attack on Medical Images: Is it Safe to Export Networks from Data Lakes? .- Data Stealing Attack on Medical Images: Is it Safe to Export Networks from Data Lakes?.- Can collaborative learning be private, robust and scalable?.- Split-U-Net: Preventing Data Leakage in Split Learning for Collaborative Multi-Modal Brain Tumor Segmentation.- Joint Multi Organ and Tumor Segmentation from Partial Labels using Federated Learning.- Fuh, Kensaku Mori, Weichung Wang, Holger R Roth GAN Latent Space Manipulation and Aggregation for Federated Learning in Medical Imaging.- A Specificity-Preserving Generative Model for Federated MRI Translation.- Content-Aware Differential Privacy with Conditional Invertible Neural Networks.- DeMed: A Novel and Efficient Decentralized Learning Framework for Medical Images Classification on Blockchain.- Cluster Based Secure Multi-Party Computation in Federated Learning for Histopathology Images.- Towards More Efficient Data Valuation in Healthcare Federated Learning using Ensembling.- Towards Real-World Federated Learning in Medical Image Analysis Using Kaapana.- Towards Sparsified Federated Neuroimaging Models via Weight Pruning.- Affordable AI and Healthcare.- Enhancing Portable OCT Image Quality via GANs for AI-Based Eye Disease Detection.- Deep Learning-based Segmentation of Pleural Effusion From Ultrasound Using Coordinate Convolutions.- Verifiable and Energy Efficient Medical Image Analysis with Quantised Self-attentive Deep Neural Networks.- LRH-Net: A Multi-Level Knowledge Distillation Approach for Low-Resource Heart Network.