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ORCIDDominik Kißkalt
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2020 – today
- 2022
[j3]Andreas Selmaier
, David Kunz, Dominik Kißkalt, Mohamed Benaziz, Jens Fürst, Jörg Franke:
Artificial Intelligence-Based Assistance System for Visual Inspection of X-ray Scatter Grids. Sensors 22(3): 811 (2022)- 2021
- [j2]Benjamin Lutz, Dominik Kißkalt, Andreas Mayr, Daniel Regulin, Matteo Pantano, Jörg Franke:
In-situ identification of material batches using machine learning for machining operations. J. Intell. Manuf. 32(5): 1485-1495 (2021) - [c5]Benjamin Lutz, Dominik Kißkalt, Daniel Regulin, Burak Aybar, Jörg Franke:
Automated Domain Adaptation in Tool Condition Monitoring using Generative Adversarial Networks. CASE 2021: 1326-1331 - [c4]Andreas Selmaier, Benjamin Lutz, Dominik Kißkalt, Simon Börnicke, Jens Fürst, Jörg Franke:
Semantic Segmentation of Multi-Channel Polycrystalline Structure Micrographs Using Convolutional Neural Networks. ICMLA 2021: 847-852 - [c3]Benjamin Lutz, Dominik Kißkalt, Daniel Regulin, Tobias Hauser, Jörg Franke:
Material Identification for Smart Manufacturing Systems: A Review. ICPS 2021: 353-360 - 2020
- [c2]Jupiter Bakakeu, Dominik Kißkalt, Jörg Franke, Shirin Baer, Hans-Henning Klos, Jörn Peschke:
Multi-Agent Reinforcement Learning for the Energy Optimization of Cyber-Physical Production Systems. CCECE 2020: 1-8
2010 – 2019
- 2019
- [c1]Benjamin Lutz, Dominik Kißkalt, Daniel Regulin, Raven Reisch, Andreas Schiffler, Jörg Franke:
Evaluation of Deep Learning for Semantic Image Segmentation in Tool Condition Monitoring. ICMLA 2019: 2008-2013 - 2018
- [j1]Dominik Kißkalt, Hans Fleischmann, Sven Kreitlein, Manuel Knott, Jörg Franke:
A novel approach for data-driven process and condition monitoring systems on the example of mill-turn centers. Prod. Eng. 12(3-4): 525-533 (2018)
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