Project Details
Description
This project investigates reconstruction methods for material testing based on surface measurements. It investigates models describing the propagation of the temperature profile and its numerical analysis. Based on this numerical analysis methods for improving the numerical properties as well as algorithms for reconstructing the material temperature profile are developed.
| Status | Finished |
|---|---|
| Effective start/end date | 01.05.2018 → 31.12.2018 |
Collaborative partners
- Johannes Kepler University Linz (lead)
- Josef Ressel Zentrum für Thermografische zerstörungsfreie Prüfung von Verbundwerkstoffen (Project partner)
Fields of science
- 202027 Mechatronics
- 202015 Electronics
- 202037 Signal processing
- 202036 Sensor systems
- 202 Electrical Engineering, Electronics, Information Engineering
- 202022 Information technology
- 202034 Control engineering
- 202017 Embedded systems
- 202030 Communication engineering
- 202028 Microelectronics
- 102019 Machine learning
- 202040 Transmission technology
- 202025 Power electronics
- 202041 Computer engineering
- 202023 Integrated circuits
JKU Focus areas
- Digital Transformation
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Surfing Virtual Waves to Thermal Tomography: From model- to deep learning-based reconstructions
Kovacs, P., Lehner, B., Thummerer, G., Mayr, G., Burgholzer, P. & Huemer, M., Jan 2022, In: IEEE Signal Processing Magazine. 39, 1, p. 55-67 13 p.Research output: Contribution to journal › Article › peer-review
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A Hybrid Approach for Thermographic Imaging With Deep Learning
Kovacs, P., Lehner, B., Thummerer, G., Mayr, G., Burgholzer, P. & Huemer, M., May 2020, Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2020). IEEE, p. 4277-4281 5 p. 9053411. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; vol. 2020-May).Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review
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Deep learning approaches for thermographic imaging
Kovacs, P., Lehner, B., Thummerer, G., Mayr, G., Burgholzer, P. & Huemer, M., 21 Oct 2020, In: Journal of Applied Physics. 128, 15, p. 155103 17 p., 155103.Research output: Contribution to journal › Article › peer-review
Activities
- 1 Invited talk
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Regularization techniques for thermographic image reconstruction
Kovacs, P. (Speaker)
14 Feb 2019Activity: Talk or presentation › Invited talk › science-to-science