TY - CONF A1 - Evsevleev, Sergei A1 - Paciornik, Sidnei A1 - Gollwitzer, Christian A1 - Bruno, Giovanni T1 - Application of deep learning to the segmentation of synchrotron X-ray tomography data of multiphase metal matrix composites N2 - The 3D microstructure of an Al alloy matrix composite with two ceramic reinforcements was investigated by synchrotron X-ray tomography. A deep learning algorithm was used for the segmentation of four different phases. We show that convolutional networks with the U-Net architecture are able to solve complex segmentation tasks with small amount of training data. T2 - International Conference on Tomography of Materials & Structures CY - Cairns, Australia DA - 22.07.2019 KW - Synchrotron X-ray tomography KW - Deep learning KW - Segmentation KW - Metal matrix composite PY - 2019 AN - OPUS4-48606 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -