Augmentation of Laser Welding Dataset through a combination of Evolutionary Optimization and Deep Learning
In this paper, we propose a method for synthetically generating industrial data based on evolutionary approaches. The method involves applying evolutionary operators to the coordinates of a polygon describing an object's shape and then transferring the original image style to the resulting polygon geometry.
Authors
- Gleb Solovev (ORCID: https://orcid.org/0009-0005-5479-2482)
- Nikolay O. Nikitin (ORCID: https://orcid.org/0000-0002-6839-9957)
- Mikhail Sokolov (ORCID: https://orcid.org/0000-0003-4413-3676)
- A. H. A. Hussein
Institutions
- ITMO University (RU)
Publication Details
- Journal
- Proceedings of the Genetic and Evolutionary Computation Conference Companion
- Published
- 2025-07-14
- DOI
- https://doi.org/10.1145/3712255.3734268
- Primary Topic
- Welding Techniques and Residual Stresses
- Type
- article
- Field-Weighted Citation Impact
- 0.00