54. Wang, Y., K. Hong, J. Zou, T. Peng, and H. Yang. 2020. “A CNN-based
visual sorting system with cloud-edge computing for flexible manu-
facturing systems.” IEEE Transactions on Industrial Informatics 16 (7):
4726–35. https://doi.org/10.1109/TII.2019.2947539
55. Feng, X., X. Gao, and L. Luo. 2021. “A ResNet50-based method for clas-
sifying surface defects in hot-rolled strip steel.” Mathematics 9 (19): 2359.
https://doi.org/10.3390/math9192359
56. Wen, L., X. Li, and L. Gao. 2020. “A transfer convolutional neural
network for fault diagnosis based on ResNet-50.” Neural Computing &
Applications 32 (10): 6111–24. https://doi.org/10.1007/s00521-019-04097-w
57. Hu, Z., Z. Yin, L. Qin, and F. Xu. 2022. “A novel method of fault
diagnosis for injection molding systems based on improved
Vgg16 and machine vision.” Sustainability (Basel) 14 (21): 14280.
https://doi.org/10.3390/su142114280
58. Ledesma, R., and A. Ramlatchan. 2021. “Convolutional Neural
Networks for Image Classification in Metal Selective Laser Melting Additive
Manufacturing.” Paper presented at the Conference on Computer Vision
and Pattern Recognition (CVPR 2021), 21–24 June, Nashville, TN.
https://ntrs.nasa.gov/citations/20205009555
59. Fakih, M. A. H., S. K. Singh, S. Mustapha, M. Radzienski, and P. H.
Malinowski. 2023. “A comprehensive analysis of guided-wave propagation
in 3D-printed PLA plates with different infill densities – Experimental
study.” Mechanical Systems and Signal Processing 202: 110645.
https://doi.org/10.1016/j.ymssp.2023.110645
60. Fakih, M. A., S. K. Singh, S. Mustapha, and P. Malinowski. 2022.
“Damage Localization in 3D-Printed Plates with Different Infill
Densities.” In Proceedings of the ASME 2022 49th Annual Review of Progress
in Quantitative Nondestructive Evaluation, pp. 52–58.
https://doi.org/10.1115/QNDE2022-95348
J U LY 2 0 2 6 • M AT E R I A L S E V A L U AT I O N 53
visual sorting system with cloud-edge computing for flexible manu-
facturing systems.” IEEE Transactions on Industrial Informatics 16 (7):
4726–35. https://doi.org/10.1109/TII.2019.2947539
55. Feng, X., X. Gao, and L. Luo. 2021. “A ResNet50-based method for clas-
sifying surface defects in hot-rolled strip steel.” Mathematics 9 (19): 2359.
https://doi.org/10.3390/math9192359
56. Wen, L., X. Li, and L. Gao. 2020. “A transfer convolutional neural
network for fault diagnosis based on ResNet-50.” Neural Computing &
Applications 32 (10): 6111–24. https://doi.org/10.1007/s00521-019-04097-w
57. Hu, Z., Z. Yin, L. Qin, and F. Xu. 2022. “A novel method of fault
diagnosis for injection molding systems based on improved
Vgg16 and machine vision.” Sustainability (Basel) 14 (21): 14280.
https://doi.org/10.3390/su142114280
58. Ledesma, R., and A. Ramlatchan. 2021. “Convolutional Neural
Networks for Image Classification in Metal Selective Laser Melting Additive
Manufacturing.” Paper presented at the Conference on Computer Vision
and Pattern Recognition (CVPR 2021), 21–24 June, Nashville, TN.
https://ntrs.nasa.gov/citations/20205009555
59. Fakih, M. A. H., S. K. Singh, S. Mustapha, M. Radzienski, and P. H.
Malinowski. 2023. “A comprehensive analysis of guided-wave propagation
in 3D-printed PLA plates with different infill densities – Experimental
study.” Mechanical Systems and Signal Processing 202: 110645.
https://doi.org/10.1016/j.ymssp.2023.110645
60. Fakih, M. A., S. K. Singh, S. Mustapha, and P. Malinowski. 2022.
“Damage Localization in 3D-Printed Plates with Different Infill
Densities.” In Proceedings of the ASME 2022 49th Annual Review of Progress
in Quantitative Nondestructive Evaluation, pp. 52–58.
https://doi.org/10.1115/QNDE2022-95348
J U LY 2 0 2 6 • M AT E R I A L S E V A L U AT I O N 53
