Quantum generative learning for high-resolution medical image generation

Integration of quantum computing in generative machine learning models has the potential to offer benefits such as training speed-up and superior feature extraction. However, the existing quantum generative adversarial networks (QGANs) fail to generate high-quality images due to their patch-based, p...

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Bibliografiske detaljer

Principais autores:	Amena Khatun, Kübra Yeter Aydeniz, Yaakov S Weinstein, Muhammad Usman
Format:	Artigo
Sprog:	Inglês
Udgivet:	IOP Publishing 2025-01-01
Serier:	Machine Learning: Science and Technology
Fag:	quantum computing quantum machine learning quantum generative learning healthcare medical image generation
Online adgang:	https://doi.org/10.1088/2632-2153/add1a9
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