DCGAN discriminator.

<div><p>Deep learning models for diagnostic applications require large amounts of sensitive patient data, raising privacy concerns under centralized training paradigms. We propose FedGAN, a federated learning framework for synthetic medical image generation that combines Generative Adver...

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التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Hassan Kamran (21782056) (author)
مؤلفون آخرون:	Syed Jawad Hussain (18106616) (author), Sohaib Latif (20314613) (author), Imtiaz Ali Soomro (21609078) (author), Mrim M. Alnfiai (19226195) (author), Nouf Nawar Alotaibi (21782059) (author)
منشور في:	2025
الموضوعات:	Microbiology Cell Biology Genetics Molecular Biology Biotechnology Science Policy Infectious Diseases Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified sensitive patient data gan &# 8217 centralized training paradigms abdominal ct scans silo federated learning federated learning framework raising privacy concerns fedgan generates high centralized discriminator ). federated averaging privacy challenges realism score propose fedgan medical ai generator via fedgan achieves experiments demonstrate approach pretrains
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DCGAN discriminator.

مواد مشابهة