Quality Data Extractor (QDE): Elevating Synthetic Data Augmentation Through Post-Generation Filtration

Synthetic data plays a crucial role in augmenting datasets for machine learning, particularly when real data is limited or sensitive. However, not all synthetic samples contribute positively to model performance; low-quality instances can degrade both predictive accuracy and data fidelity. To addres...

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Podrobná bibliografie

Hlavní autoři:	Pragati Sachdeva, Amarjit Malhotra, Karan Gupta
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	IEEE 2025-01-01
Edice:	IEEE Access
Témata:	Data augmentation generative adversarial networks classification prediction structured data
On-line přístup:	https://ieeexplore.ieee.org/document/11142788/
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