Automated defect inspection of LED chip using deep convolutional neural network

Chang, C. Y., Chang, C. H., Li, C. H., & De Jeng, M. (2007). Learning vector quantization neural networks for LED wafer defect inspection. In Second international conference on innovative computing, information and control, 2007. ICICIC ’07, p. 229.

Choi, K. J., Lee, Y. H., Moon, J. W., Park, C. K., & Harashima, F. (2007). Development of an automatic stencil inspection system using modified Hough transform and fuzzy logic. IEEE Transactions on Industrial Electronics, 54(1), 604–611.

Deng, J., et al. (2009). ImageNet: A large-scale hierarchical image database. In IEEE conference on computer vision and pattern recognition, pp. 248–255.

Everingham, M., Gool, L. V., & Williams, C. K. I. (2010). The pascal visual object classes (VOC) challenge. International Journal of Computer Vision, 88(2), 303–338.

Hinton, G. E., Srivastava, N., Krizhevsky, A., Sutskever, I., & Salakhutdinov, R. R. (2012). Improving neural networks by preventing co-adaptation of feature detectors. arXiv preprint.

Imamoglu, N., Kimura, M., Miyamoto, H., Fujita, A., & Nakamura, R. (2017). Solar power plant detection on multi-spectral satellite imagery using convolutional neural network with feedback model and m-PCNN fusion. arXiv preprint.

Jia, Y. Q., et al. (2014). Caffe: Convolutional architecture for fast feature embedding. In Proceedings of the 22nd ACM international conference on multimedia, pp. 675–678.

Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2012). Imagenet classification with deep convolutional neural network. In A. Krizhevsky & I. Sutskever (Eds.), International conference on neural information processing systems, pp. 1097–1105.

Kumar, A. (2008). Computer-vision-based fabric defect detection: A survey. IEEE Transactions on Industrial Electronics, 55(1), 348–363.

Kuo, C. F. J., Hsu, C. T. M., Liu, Z. X., & Wu, H. C. (2014). Automatic inspection system of LED chip using two-stages back-propagation neural network. Journal of Intelligent Manufacturing, 25(6), 1235–1243.

LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436–444.

Li, W., Leonardis, A., & Fritz, M. (2016). Visual stability prediction and its application to manipulation. arXiv preprint.

Lin, C. H. (2006). Digital-dimming controller with current spikes elimination technique for LCD backlight electronic ballast. IEEE Transactions on Industrial Electronics, 53(6), 1881–1888.

Lin, H. D. (2009). Automated defect inspection of light-emitting diode chips using neural network and statistical approaches. Expert Systems with Applications, 36(1), 219–226.

Lo, Y. K., Wu, K. H., Pai, K. J., & Chiu, H. J. (2009). Design and implementation of RGB LED drivers for LCD backlight modules. IEEE Transactions on Industrial Electronics, 56(12), 4862–4871.

Otsu, N. (1975). A threshold selection method from gray-level histograms. IEEE Transactions on Systems, Man, and Cybernetics, 11, 23–27.

Ruhmelhart, D. E., Hinton, G. E., & Wiliams, R. J. (1986). Learning representations by back-propagation errors. Nature, 323, 533–536.

Schubert, E. F., Gessmann, T., & Kim, J. K. (2006). Light-emitting diodes. Cambridge: Cambridge Univ. Press.

Sermanet, P., Eigen, D., Zhang, X., Mathieu, M ., Fergus, R., & LeCun, Y. (2013). Overfeat: Integrated recognition, localization and detection using convolutional networks. arXiv preprint.

Simonyan, K., & Zisserman, A. (2015). Very deep convolutional networks for large-scale image recognition. arXiv preprint.

Szegedy, C., et al. (2015). Going deeper with convolutions. In The IEEE conference on computer vision and pattern recognition, pp. 1–9.

Szeliski, R. (2010). Computer vision: Algorithms and applications. London: Springer Science Business Media.

Tsai, D. M., Chiang, I. Y., & Tsai, Y. H. (2012). A shift-tolerant dissimilarity measure for surface defect detection. IEEE Transactions on Industrial Informatics, 8(1), 128–137.

Wendt, M., & Andriesse, J. W.(2006). LEDs in real lighting applications: From niche markets to general lighting. In Industry Applications Conference, 2006. 41st IAS Annual Meeting. Conference Record of the 2006 IEEE, Vol. 5, pp. 2601–2603.

Wu, X. K., Hu, C., Zhang, J. M., & Zhao, C. (2014). Series-parallel autoregulated charge-balancing rectifier for multioutput light-emitting diode driver. IEEE Transactions on Industrial Electronics, 61(3), 1262–1268.

Wu, C. Y., Wu, T. F., Tsai, J. R., Chen, Y. M., & Chen, C. C. (2008). Multistring LED backlight driving system for LCD panels with color sequential display and area control. IEEE Transactions on Industrial Electronics, 55(10), 3791–3800.

Zhong, F. Q., He, S. P., & Li, B. (2017). Blob analyzation-based template matching algorithm for LED chip localization. The International Journal of Advanced Manufacturing Technology, 93, 55–63.

Zhou, B., Khosla, A., Lapedriza, A., Oliva, A., & Torralba, A. (2016). Learning deep features for discriminative localization. In The IEEE conference on computer vision and pattern recognition, pp. 2921–2929.