Michael Friedrich
Orcid: 0000-0001-6326-4749Affiliations:
- Chemnitz University of Technology, Germany
According to our database1,
Michael Friedrich
authored at least 4 papers
between 2019 and 2022.
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Bibliography
2022
Improving automated visual fault inspection for semiconductor manufacturing using a hybrid multistage system of deep neural networks.
J. Intell. Manuf., 2022
2020
Improving Automated Visual Fault Detection by Combining a Biologically Plausible Model of Visual Attention with Deep Learning.
Proceedings of the 46th Annual Conference of the IEEE Industrial Electronics Society, 2020
2019
Hexagonal Image Processing in the Context of Machine Learning: Conception of a Biologically Inspired Hexagonal Deep Learning Framework.
Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019
A Novel Visual Fault Detection and Classification System for Semiconductor Manufacturing Using Stacked Hybrid Convolutional Neural Networks.
Proceedings of the 24th IEEE International Conference on Emerging Technologies and Factory Automation, 2019