Classification of Chopped Strand Mat Defects Based on Convolutional Neural Network

Dong Zhuo; Junfeng Jing; Huanhuan Zhang; Zebin Su

doi:10.3788/LOP56.101009

[1] Deng H P, Bo S Q[J]. Correlation offiberglass chopped strand mat strength with its binder Fiber Glass, 2015, 18-21.

[2] Zhang J Y, Jing J F. Defect classification of chopped strand mats based on deep learning and piecewise linear interpolation[J]. Journal of Xi'an Polytechnic University, 32, 553-559(2018).

[3] Szegedy C, Liu W, Jia Y Q, Pattern Recognition, 7-12 June et al. Boston, MA, USA. New York: IEEE, 15523970(2015).

[4] Du J, Hu B L, Zhang Z F. Gastriccarcinoma classification based on convolutional neural network and micro-hyperspectral imaging[J]. Acta Optica Sinica, 38, 0617001(2018).

[5] Chu J H, Wu Z R, Lü W et al. Breast cancer diagnosis system based on transfer learning and deep convolutional neural networks[J]. Laser & Optoelectronics Progress, 55, 081001(2018).

[6] Jing J F, Fan X T, Li P F. Patterned fabric defect detection via convolutional matching pursuit dual-dictionary[J]. Optical Engineering, 55, 053109(2016). http://proceedings.spiedigitallibrary.org/article.aspx?articleid=2526411&resultClick=1

[7] Fang X, Wang G H, Yang H C et al. High resolution remote sensing image classification combining with mean-shift segmentation and fully convolution neural network[J]. Laser & Optoelectronics Progress, 55, 022802(2018).

[8] Lai W H, Zhou M R, Wang Y et al. Application of counterfeit liquor recognition based on deep learning and laser induced fluorescence[J]. Laser & Optoelectronics Progress, 55, 043001(2018).

[9] LeCun Y, Boser B, Denker J S et al. . Backpropagation applied to handwritten zip code recognition[J]. Neural Computation, 1, 541-551(1989). http://dl.acm.org/citation.cfm?id=1351090&preflayout=flat

[10] Yang W, Wanli O Y, Li H S, Pattern Recognition, 27-30 June et al. Las Vegas, NV, USA. New York: IEEE, 16541427(2016).

[11] Zeiler M D, Fergus R[M]. Visualizing and understanding convolutional networks, 818-833(2014).

[12] Krizhevsky A, Sutskever I, Hinton G E. ImageNet classification with deep convolutional neural networks. [C]∥International Conference on Neural Information Processing Systems. Dickinson: Curran Associates Inc., 1097-1105(2012).

[13] Hearst M A, Dumais S T, Osuna E et al. Support vector machines[J]. IEEE Intelligent Systems and their Applications, 13, 18-28(1998).

[14] Oquab M, Bottou L, Laptev I, Pattern Recognition, 23-28 June et al. Columbus, OH, USA. New York: IEEE, 14632209(2014).

[15] Donahue J, Hendricks L A, Rohrbach M et al. Long-term recurrent convolutional networks for visual recognition and description[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 677-691(2017). http://ieeexplore.ieee.org/document/7558228

[16] Wang Z, Crammer K, Vucetic S. Breaking the curse of kernelization: budgeted stochastic gradient descent for large-scale SVM training[J]. Journal of Machine Learning Research, 13, 3103-3131(2012). http://dl.acm.org/citation.cfm?id=2503308.2503341&coll=DL&dl=GUIDE&CFID=412270470&CFTOKEN=84231780