News from SDL: Have a look at the new article

News from our Simulation and Data Lab Materials Design: Have a look at the article “A deep learned nanowire segmentation model using synthetic data augmentation“, which was recently published in Npj Computational Materials and in the interactive segmentation tool https://lnkd.in/eMYYe5Jv The computing time for this research was provided on the supercomputer Lichtenberg II at Technische Universität Darmstadt Automated particle segmentation and feature analysis of experimental image data is a big challenge in data-driven material science. In the present work, the SDL Materials Design applies synthetic images that resemble the experimental images in terms of geometrical and visual features, to train the state-of-art Mask region-based convolutional neural networks (Mask R-CNN) to segment densely packed nanowires from battery electrode materials in different types of microscopy images. The proposed methodology can be extended to any optical intensity-based images of variable particle morphology, material class, and beyond… Read more at: https://rdcu.be/cMwcw The research was done by Binbin Lin and his collaborators.