Open Access
| Issue |
MATEC Web Conf.
Volume 349, 2021
6th International Conference of Engineering Against Failure (ICEAF-VI 2021)
|
|
|---|---|---|
| Article Number | 02021 | |
| Number of page(s) | 8 | |
| Section | Metallic Materials: Characterization, Mechanical Behavior and Modeling, Detection of Metal Failures | |
| DOI | https://doi.org/10.1051/matecconf/202134902021 | |
| Published online | 15 November 2021 | |
- M.T.N. Truong, S. Kim, Automatic image thresholding using Otsu!s method and entropy weighting scheme for surface defect detection, Soft Comput 22, 4197-4203 (2018) [CrossRef] [Google Scholar]
- L. Song, W. Lin, Y. Tang, X. Zhu, Q. Guo, J. Xi, IEEE Access, 7, 27547-27554 (2019) [CrossRef] [Google Scholar]
- B. Dipert, Beyond-visible Light Applications in Computer Vision, Embedded Vision Alliance (2017) [Google Scholar]
- A. Ajgaonkar, K. Seier, The Value of Computer Vision: more Than Meets The Eye, Insight Tech Journal, Spring (2021) [Google Scholar]
- COGNEX Corp., Introduction To Machine Vision: A guide to automating process & quality improvements, 6 (2016) [Google Scholar]
- T.S. Huang, Computer Vision Evolution and Promise, CERN-96-08, 21-27, (1996) [Google Scholar]
- B. Anthony, MIT Professional Education: Smart Manufacturing. Week 6 Slides, (2019) [Google Scholar]
- L.G. Shapiro, G.C. Stockman, Computer Vision, 33-60, (2001) [Google Scholar]
- A.K. Maini, Image Processing Using MATLAB: Basic Operations, (Part 1 of 4) electronicsforu.com (2019) [Google Scholar]
- E.R. Davies, Computer Vision: Principles, Algorithms, Applications, Learning,190-192 (2018) [Google Scholar]
- L.S. Athanasiou, D.I. Fotiadis, L.K. Michalis, 4- Plaque Characterization Methods Using Intravascular Ultrasound Imaging, Atherosclerotic Plaque Characterization Methods Based on Coronary Imaging, Academic Press, 71-94 (2017) [CrossRef] [Google Scholar]
- P. Deka, R. Mittal, Quality inspection in manufacturing using deep learning based computer vision: Improving yield by removing bad quality material with image recognition, Toward Data Science, December (2018) [Google Scholar]
- G. Gonzáles, J. González, et al. Measuring elastoplastic strain loops in the near crack-tip region using a Stereo Microscope DIC system, Int J. Fatigue, 133 105427 (2020) [CrossRef] [Google Scholar]
- M.A. Sutton, J.J. Orteu, H. Schreier, Image Correlation for Shape, Motion and Deformation Measurements: Basic Concepts, Theory and Applications. Springer (2009) [Google Scholar]
- J. Tong, B. Lin, et al. Near-tip strain evolution under cyclic loading: In situ experimental observation and numerical modelling. Int J. Fatigue, 71, 45–52 (2015) [CrossRef] [Google Scholar]
- Y. Zhu, Z. Wu, W.D. Hartley, et al. Unraveling pore evolution in post-processing of binder jetting materials: X-ray computed tomography, computer vision, and machine learning, Additive Manufacturing, 34, 101183, (2020) [CrossRef] [Google Scholar]
- M. Enikeev, I. Gubaydullin, M. Maleeva, Analysis of Corrosion Process Development on Metals by Means of Computer Vision, Engineering Journal 21, 183-192 (2017) [CrossRef] [Google Scholar]
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