Addressing data scarcity in nanomaterial segmentation networks with differentiable rendering and generative modeling

Abstract Nanomaterials’ properties, influenced by size, shape, and surface characteristics, are crucial for their technological, biological, and environmental applications. Accurate quantification of these materials is essential for advancing research. Deep learning segmentation networks offer preci...

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Główni autorzy:	Dennis Possart, Leonid Mill, Florian Vollnhals, Tor Hildebrand, Peter Suter, Mathis Hoffmann, Jonas Utz, Daniel Augsburger, Mareike Thies, Mingxuan Gu, Fabian Wagner, George Sarau, Silke Christiansen, Katharina Breininger
Format:	Artigo
Język:	Inglês
Wydane:	Nature Portfolio 2025-07-01
Seria:	npj Computational Materials
Dostęp online:	https://doi.org/10.1038/s41524-025-01702-6
Etykiety:	Dodaj etykietę Nie ma etykietki, Dołącz pierwszą etykiete!