TY - CONF A1 - Karapanagiotis, Christos T1 - Evaluation of the generalization performance of a CNN-assisted BOFDA system N2 - Brillouin Optical Frequency Domain Analysis (BOFDA) is a powerful and well-established method for static distributed sensing of temperature and strain. Recently, we demonstrated a BOFDA system based on convolutional neural network which shortens the measurement time considerably. In this paper, we apply leave-one-out cross validation to evaluate the generalization performance and provide an unbiased and reliable machine learning model for a time-efficient BOFDA system. T2 - 21. ITG/GMA Fachtagung Sensoren und Messsysteme 2022 CY - Nürnberg, Germany DA - 10.05.2022 KW - Fiber optics sensors KW - BOFDA KW - Convolutional neural networks KW - Machine learning KW - Temperature sensing PY - 2022 AN - OPUS4-54862 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -