Research data - Generative adversarial networks for creating realistic training data for machine learning-based segmentation of FIB tomography data

Sardhara, TrushalTrushalSardhara2025-01-222025-01-222025-01-22https://tore.tuhh.de/handle/11420/53280This dataset contains simulated and domain-adapted multi-voltage FIB tomography data on hierarchical nanoporous gold, trained machine learning model weights, and segmentation results of synthetic and real hierarchical nanoporous gold data. For more information, please refer to the published research article: Generative adversarial networks for creating realistic training data for machine learning-based segmentation of FIB tomography datahttps://creativecommons.org/licenses/by/4.0/Domain adaptationFast simulationSynthetic dataFIB-SEM tomography3D reconstructionTechnology::620: Engineering::620.1: Engineering Mechanics and Materials ScienceResearch data - Generative adversarial networks for creating realistic training data for machine learning-based segmentation of FIB tomography dataDatasethttps://doi.org/10.15480/882.1434410.15480/882.14344