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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Veröffentlicht in:	JPhys photonics Jg. 7; H. 4; S. 42002 - 42018
Hauptverfasser:	Yogita, Yogita, Bocklitz, Thomas
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Bristol IOP Publishing 31.10.2025
Schlagworte:	Deep learning Imaging inverse problems machine learning optical and photonic data Physics physics-informed deep learning
ISSN:	2515-7647, 2515-7647
Online-Zugang:	Volltext
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