Deep-Learning-Driven Techniques for Real-Time Multimodal Health and Physical Data Synthesis

Deep-Learning-Driven Techniques for Real-Time Multimodal Health and Physical Data Synthesis

With the advent of Artificial Intelligence for healthcare, data synthesis methods present crucial benefits in facilitating the fast development of AI models while protecting data subjects and bypassing the need to engage with the complexity of data sharing and processing agreements. Existing technol...

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Bibliographic Details
Main Authors: Muhammad Salman Haleem, Audrey Ekuban, Alessio Antonini, Silvio Pagliara, Leandro Pecchia, Carlo Allocca
Format: Article
Language:English
Published: MDPI AG 2023-04-01
Series:Electronics
Subjects:
synthetic data generation
augmented data
temporally correlated generative adversarial networks
text generative models
deep learning
Online Access:https://www.mdpi.com/2079-9292/12/9/1989

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https://www.mdpi.com/2079-9292/12/9/1989

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