Brand S, Koegel M, Altmann F, Bach L (2021)
Publication Type: Conference contribution
Publication year: 2021
Publisher: IEEE COMPUTER SOC
City/Town: LOS ALAMITOS
Pages Range: 877-884
Conference Proceedings Title: IEEE 71ST ELECTRONIC COMPONENTS AND TECHNOLOGY CONFERENCE (ECTC 2021)
Event location: , ELECTR NETWORK
DOI: 10.1109/ECTC32696.2021.00147
APA:
Brand, S., Koegel, M., Altmann, F., & Bach, L. (2021). Deep Learning assisted quantitative Assessment of the Porosity in Ag-Sinter joints based on non-destructive acoustic inspection. In IEEE 71ST ELECTRONIC COMPONENTS AND TECHNOLOGY CONFERENCE (ECTC 2021) (pp. 877-884). , ELECTR NETWORK: LOS ALAMITOS: IEEE COMPUTER SOC.
MLA:
Brand, Sebastian, et al. "Deep Learning assisted quantitative Assessment of the Porosity in Ag-Sinter joints based on non-destructive acoustic inspection." Proceedings of the IEEE 71st Electronic Components and Technology Conference (ECTC), , ELECTR NETWORK LOS ALAMITOS: IEEE COMPUTER SOC, 2021. 877-884.
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