Anomaly Detection with Decision Trees for AI Assisted Evaluation of Signal Integrity on PCB Transmission Lines by E. Ecik, W. John, J. Withöft, J. Götze

“…In this paper, a decision tree for anomaly detection and SI verification is presented, which by nature of this algorithm provides insights to the decisions made to obtain the proposed design parameters. …”
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Automated woven background removal for enhanced infrared thermographic inspection of fabric composites by Gaétan Poelman, Saeid Hedayatrasa, Mathias Kersemans

“…Their inspection is typically characterised by the presence of an imprint of the weave pattern in the thermographic recordings, which is most-often found to be disturbing for reliable anomaly detection. In this contribution, it is proposed to evaluate the thermographic data in ????…”
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A Machine Learning Based-Guided Wave Approach for Damage Detection and Assessment in Composite Overwrapped Pressure Vessels by Amir Charmi, Samir Mustapha, Bengisu Yilmaz, Jan Heimann, Jens Prager

“…Two ML algorithms are used in the automated evaluation procedure (i) a long short-term memory (LSTM) autoencoder for anomaly detection (defects/impact), and (ii) a convolutional neural network (CNN) model for feature extraction and classification of the artificial damage sizes and locations. …”
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Gebelein Archaeological Project in 2019: Northern necropolis and the temple complex by Wojciech Ejsmond, Olivier Pierre Rochecouste, Taichi Kuronuma, Piotr Witkowski

“…Continued archaeological surveys at two sites in the Gebelein area, the Northern Necropolis and the temple complex, have contributed new data for a better understanding of the ancient remains. Geophysical anomalies detected in 2015 in the western part of the Northern necropolis should now be interpreted most probably as tombs with mud-brick walls. …”
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Reduction of rejects by combining data from the casting process and automatic X-ray inspection by Thomas Stocker, Frank Sukowski, Julius Mehringer, Henning Frechen, Felix Schäfer, Dennis Freier

“…We apply a combination of layer-wise relevance propagation and dimensionality reduction to find correlations between data of the casting machines (process and sensor) and the characteristics of anomalies detected during X-ray inspection. With this information, it is possible to adjust the casting process in an early stage – even before rejects are produced. …”
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