Deep-Learning-Based Computer Vision System for Surface-Defect Detection

Author:

Tabernik Domen,Šela Samo,Skvarč Jure,Skočaj Danijel

Publisher

Springer International Publishing

Reference12 articles.

1. Abadi, M., et al.: TensorFlow: large-scale machine learning on heterogeneous systems (2015). https://www.tensorflow.org/

2. Chen, P.H., Ho, S.S.: Is overfeat useful for image-based surface defect classification tasks? In: IEEE International Conference on Image Processing, pp. 749–753 (2016)

3. Cognex: VISIONPRO VIDI: deep learning-based software for industrial image analysis (2018). https://www.cognex.com/products/machine-vision/vision-software/visionpro-vidi

4. Faghih-Roohi, S., Hajizadeh, S., Núñez, A., Babuska, R., Schutter, B.D.: Deep convolutional neural networks for detection of rail surface defects deep convolutional neural networks for detection of rail surface defects. In: International Joint Conference on Neural Networks, pp. 2584–2589, October 2016

5. Ghazvini, M., Monadjemi, S.A., Movahhedinia, N., Jamshidi, K.: Defect detection of tiles using 2D-wavelet transform and statistical features. Int. Schol. Sci. Res. Innov. 3(1), 773–776 (2009)

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