Bickel S, Schleich B, Wartzack S (2022)
Publication Type: Conference contribution
Publication year: 2022
Publisher: Cambridge University Press
Book Volume: 2
Pages Range: 1501-1510
Conference Proceedings Title: Proceedings of the Design Society
DOI: 10.1017/pds.2022.152
Digital engineering is increasingly established in the industrial routine. Especially the application of machine learning on geometry data is a growing research issue. Driven by this, the paper presents a new method for the classification of mechanical components, which utilizes the projection of points onto a spherical detector surfaces to transfer the geometries into matrices. These matrices are then classified using deep learning networks. Different types of projection are examined, as are several deep learning models. Finally, a benchmark dataset is used to demonstrate the competitiveness.
APA:
Bickel, S., Schleich, B., & Wartzack, S. (2022). A New Projection Based Method for the Classification of Mechanical Components Using Convolutional Neural Networks. In Proceedings of the Design Society (pp. 1501-1510). Online, HR: Cambridge University Press.
MLA:
Bickel, Sebastian, Benjamin Schleich, and Sandro Wartzack. "A New Projection Based Method for the Classification of Mechanical Components Using Convolutional Neural Networks." Proceedings of the 17th International Design Conference, DESIGN 2022, Online Cambridge University Press, 2022. 1501-1510.
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