Sequence of U-Shaped Convolutional Networks for Assessment of Degree of Delamination Around Scribe

Autor: Veronika Rozsivalova, Petr Dolezel, Dominik Stursa, Pavel Rozsival
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: International Journal of Computational Intelligence Systems, Vol 15, Iss 1, Pp 1-11 (2022)
Druh dokumentu: article
ISSN: 1875-6883
DOI: 10.1007/s44196-022-00141-1
Popis: Abstract The application of protective layers is the primary method of keeping metallic structures resistant to degradation. The measurement of the layer resistance to delamination is one of the important indicators of the protection quality. Therefore, ISO 4628 standard has been issued to handle and quantify the main coating defects. Here, an innovative assessment of degree of delamination around a scribe according to ISO 4628 standard has been practically realized. It utilizes an computer-driven deep learning-based method. The assessment method is composed of two shallow U-shaped convolutional networks in a row; the first for preliminary and the second for refined detection of delamination area around a scribe. The experiments performed on 586 samples showed that the proposed sequence of U-shaped convolutional networks meets the edge computing standards, provides good generalization capability, and provides precise delamination area detection for a large variability of surfaces.
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