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

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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Main Authors: 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: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:npj Computational Materials
Online Access:https://doi.org/10.1038/s41524-025-01702-6
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https://doi.org/10.1038/s41524-025-01702-6

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