Advances in physics-informed deep learning for imaging data: a review of methods and applications

Deep learning (DL) has transformed numerous application domains owing its ability to automatically extract features from data. However, training DL models typically requires large datasets, which are often unavailable for scientific research. In recent years, the integration of physics with DL, know...

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Vydané v:	JPhys photonics Ročník 7; číslo 4; s. 42002 - 42018
Hlavní autori:	Yogita, Yogita, Bocklitz, Thomas
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Bristol IOP Publishing 31.10.2025
Predmet:	Deep learning Imaging inverse problems machine learning optical and photonic data Physics physics-informed deep learning
ISSN:	2515-7647, 2515-7647
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