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Dataset used in the research presented in the article: Szymanik, Barbara. 2022. "An Evaluation of 3D-Printed Materials’ Structural Properties Using Active Infrared Thermography and Deep Neural Networks Trained on the Numerical Data" Materials 15, no. 10: 3727. https://doi.org/10.3390/ma15103727 The database in the .mat (matlab) format contains arrays of double type related to: A - original thermograms obtained for the plate made with the 3D printing technique Ar - thermograms with ROI included FITorg - approximation of original thermograms ImDiff, ImInt, ImProp - data obtained after subtracting the approximation.
This research was funded by the National Science Center, Poland (Narodowe Centrum Nauki, NCN), within the research project "Evaluation of the internal structure and assessment of the structure health of complex materials using active infrared thermography with multiple excitation sources", grant number 2020/04/X/ST7/01388. The APC was funded by the Research Fund of the Faculty of Electrical Engineering (West Pomeranian University of Technology, Szczecin, Poland).
deep learning;, LSTM neural networks;, 3D-printed structure quality, numerical modeling;, active thermography;
deep learning;, LSTM neural networks;, 3D-printed structure quality, numerical modeling;, active thermography;
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