Open Access
| Issue |
E3S Web Conf.
Volume 698, 2026
First International Conference on Research and Advancements in Electronics, Energy, and Environment (ICRAEEE 2025)
|
|
|---|---|---|
| Article Number | 01001 | |
| Number of page(s) | 5 | |
| Section | Electrical and Electronic Engineering | |
| DOI | https://doi.org/10.1051/e3sconf/202669801001 | |
| Published online | 16 March 2026 | |
- N. Faisal et al., ‘Defect Types’, in Structural Health Monitoring Damage Detection Systems for Aerospace, M. G. R. Sause and E. Jasiūnienė, Eds, Cham: Springer International Publishing, 2021, pp. 15–72. doi: 10.1007/978-3-030-72192-3_3. [Google Scholar]
- ‘Image Classification based on CNN: Models and Modules’, in ResearchGate, doi: 10.1109/BDICN55575.2022.00134. [Google Scholar]
- O. Mesbahi, S. Chabane, N. P. Santos, A. D. P. Lino, M. Tlemçani, and J. M. L. Da Saúde, ‘Automated Detection of Aircraft Surface Defects Using Deep Learning with Integrated Human Validation’, in 2025 13th International Conference on Systems and Control (ICSC), Oct. 2025, pp. 13–18. doi: 10.1109/ICSC67755.2025.11335094. [Google Scholar]
- S. Chabane, O. Mesbahi, N. P. Santos, M. Tlemcani, and J. L. de Saude, ‘Detection and Classification of Aircraft Structural Defects for Database Creation and Findings Identification’, in 2025 13th International Conference on Systems and Control (ICSC), Oct. 2025, pp. 144–149. doi: 10.1109/ICSC67755.2025.11335084. [Google Scholar]
- ‘Roboflow: Computer vision tools for developers and enterprises’. Accessed: Jun. 03, 2025. [Online]. Available: https://roboflow.com [Google Scholar]
- J. K. Balangao, ‘Corrosion of Metals: Factors, Types and Prevention Strategies’, vol. 14, pp. 79–87, Jan. 2024. [Google Scholar]
- A. E. Rodríguez-Sánchez, E. Ledesma-Orozco, and S. Ledesma, ‘Part distortion optimization of aluminum-based aircraft structures using finite element modeling and artificial neural networks’, CIRP Journal of Manufacturing Science and Technology, vol. 31, pp. 595–606, Nov. 2020, doi: 10.1016/j.cirpj.2020.08.011. [Google Scholar]
- Z. Yang, Y. Zhao, and C. Xu, ‘Detection of Missing Bolts for Engineering Structures in Natural Environment Using Machine Vision and Deep Learning’, Sensors, vol. 23, no. 12, Art. no. 12, Jan. 2023, doi: 10.3390/s23125655. [Google Scholar]
- Y. Berthier, L. Vincent, and M. Godet, ‘Fretting fatigue and fretting wear’, Tribology International, vol. 22, no. 4, pp. 235–242, Aug. 1989, doi: 10.1016/0301-679X(89)90081-9. [Google Scholar]
- ‘Repairing Sheet Metal - Dealing with dents, scratches, cracks, and missing rivets’. Accessed: Nov. 04, 2024. [Online]. Available: https://www.eaa.org/eaa/aircraft-building/builderresources/while-youre-building/building-articles/metal/repairing-sheet-metal [Google Scholar]
- D. Chen and J. Schijve, Bulging of fatigue cracks in a pressurized aircraft fuselage. 1991, pp. 277–315. Accessed: Nov. 04, 2024. [Online]. Available: https://ui.adsabs.harvard.edu/abs/1991afks.proc..277C [Google Scholar]
- K. Shunmugapriya, S. S. Kale, G. Gouda, P. Jayapal, and K. Tamilmani, ‘Paints for Aerospace Applications’, in Aerospace Materials and Material Technologies : Volume 1: Aerospace Materials, N. E. Prasad and R. J. H. Wanhill, Eds, Singapore: Springer, 2017, pp. 539–562. doi: 10.1007/978-981-10-2134-3_25. [Google Scholar]
- ‘AEROMEC – The Aero Maintenance Experts Company’, Aeromec. Accessed: Jun. 03, 2025. [Online]. Available: https://www.aeromec.pt/ [Google Scholar]
- ‘Forms of Aircraft Corrosion’, Aircraft Systems. Accessed: Jun. 12, 2025. [Online]. Available: http://www.aircraftsystemstech.com/2019/04/forms-of-corrosion-aircraft-corrosion.html [Google Scholar]
- J. Barnes, ‘“Restoring Aircraft Paint: Tips for a Pristine Finish” - SkySift’. Accessed: Oct. 23, 2024. [Online]. Available: https://skysift.com/restoring-aircraft-paint-tips-for-a-pristine-finish/ [Google Scholar]
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