Classification of surface defects on steel sheet using convolutional neural networks
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Youping Chen | Yunfei Zhou | Dailin Zhang | Jingming Xie | Shiyang Zhou | Youping Chen | Jingming Xie | Dailin Zhang | Shiyang Zhou | Yunfei Zhou
[1] Ke Xu,et al. Application of multi-scale feature extraction to surface defect classification of hot-rolled steels , 2013, International Journal of Minerals, Metallurgy, and Materials.
[2] Yunhui Yan,et al. A noise robust method based on completed local binary patterns for hot-rolled steel strip surface defects , 2013 .
[3] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[4] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[5] Geoffrey E. Hinton,et al. Learning representations by back-propagating errors , 1986, Nature.
[6] Yoshua Bengio,et al. Practical Recommendations for Gradient-Based Training of Deep Architectures , 2012, Neural Networks: Tricks of the Trade.
[7] David J. Field,et al. Emergence of simple-cell receptive field properties by learning a sparse code for natural images , 1996, Nature.
[8] Dragana Brzakovic,et al. Designing a defect classification system: A case study , 1996, Pattern Recognit..
[9] D Jeulin,et al. Texture classification by statistical learning from morphological image processing: application to metallic surfaces , 2010, Journal of microscopy.
[10] Praminda Caleb-Solly,et al. Adaptive surface inspection via interactive evolution , 2007, Image Vis. Comput..
[11] Peter Glöckner,et al. Why Does Unsupervised Pre-training Help Deep Learning? , 2013 .
[12] Trevor Darrell,et al. DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition , 2013, ICML.
[13] P. Caleb,et al. Classification of surface defects on hot rolled steel using adaptive learning methods , 2000, KES'2000. Fourth International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies. Proceedings (Cat. No.00TH8516).
[14] Qian Huang,et al. Improving Automatic Detection of Defects in Castings by Applying Wavelet Technique , 2006, IEEE Transactions on Industrial Electronics.
[15] Yuanxiang Li,et al. Classification of defects in steel strip surface based on multiclass support vector machine , 2014, Multimedia Tools and Applications.
[16] Pascal Vincent,et al. Representation Learning: A Review and New Perspectives , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[17] Ruiyu Liang,et al. A vision inspection system for the surface defects of strongly reflected metal based on multi-class SVM , 2011, Expert Syst. Appl..
[18] Maoxiang Chu,et al. Strip Steel Surface Defect Classification Method Based on Enhanced Twin Support Vector Machine , 2014 .
[19] Anirban Mukherjee,et al. Automatic Defect Detection on Hot-Rolled Flat Steel Products , 2013, IEEE Transactions on Instrumentation and Measurement.
[20] C.S. Lee,et al. Feature extraction algorithm based on adaptive wavelet packet for surface defect classification , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.
[21] Tony Lindeberg,et al. An automatic assessment scheme for steel quality inspection , 2000, Machine Vision and Applications.
[22] Matti Pietikäinen,et al. Automated visual inspection of rolled metal surfaces , 1990, Machine Vision and Applications.
[23] Du-Ming Tsai,et al. Automated surface inspection for statistical textures , 2003, Image Vis. Comput..
[24] Rob Fergus,et al. Visualizing and Understanding Convolutional Networks , 2013, ECCV.
[25] Guigang Zhang,et al. Deep Learning , 2016, Int. J. Semantic Comput..
[26] Xindong Wu,et al. Plant Leaf Identification via a Growing Convolution Neural Network with Progressive Sample Learning , 2014, ACCV.