Automated Industrial Defect Detection and Accurate Fractional-Grade  Classification

M. Ramana Kumar, S. Sreenath Kashyap

Automated Industrial Defect Detection and Accurate Fractional-Grade Classification

Authors

M. Ramana Kumar, S. Sreenath Kashyap

Keywords:

Automated Quality Control, Magnetic Tile Defect Classification, Computer Vision Pipeline, SVM Classifier, Random Forest Ensemble.

Abstract

In modern industrial manufacturing, ensuring the structural integrity of magnetic tiles is essential, assurface defects can severely compromise electromagnetic performance and operational reliability. Traditional manual visual inspection methods are inherently slow

References

Li F., Mao Q., and Chang C.-C., Reversible data hiding scheme based on the Haar discrete wavelet transform and interleaving prediction method, Multimedia Tools and Applications, 77, 5149–5168

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Published

2024-11-20

How to Cite

M. Ramana Kumar, S. Sreenath Kashyap. (2024). Automated Industrial Defect Detection and Accurate Fractional-Grade Classification . Journal of Computational Analysis and Applications (JoCAAA), 33(08), 9008–9019. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/5613