Deep Learning-Based Domain Adaptation Method for Fault Diagnosis in Semiconductor Manufacturing

作者: Moslem Azamfar , Xiang Li , Jay Lee

DOI: 10.1109/TSM.2020.2995548

关键词:

摘要: … distribution … distribution discrepancies and therefore it can effectively adjust for a specific transfer task. In this study, MMD is used to compute the marginal and conditional distribution …

参考文章(40)
P. G. Stoica, Randolph L. Moses, Spectral analysis of signals ,(2005)
Kevin Swersky, Yujia Li, Rich Zemel, Rich Zemel, Generative Moment Matching Networks international conference on machine learning. pp. 1718- 1727 ,(2015)
Ridha Ziani, Ahmed Felkaoui, Rabah Zegadi, Bearing fault diagnosis using multiclass support vector machines with binary particle swarm optimization and regularized Fisher's criterion Journal of Intelligent Manufacturing. ,vol. 28, pp. 405- 417 ,(2017) , 10.1007/S10845-014-0987-3
Mingsheng Long, Jianmin Wang, Guiguang Ding, Jiaguang Sun, Philip S. Yu, Transfer Feature Learning with Joint Distribution Adaptation international conference on computer vision. pp. 2200- 2207 ,(2013) , 10.1109/ICCV.2013.274
Ravi Janardan, Qi Li, Jieping Ye, Two-Dimensional Linear Discriminant Analysis neural information processing systems. ,vol. 17, pp. 1569- 1576 ,(2004)
Kenji Fukumizu, Bharath K. Sriperumbudur, Dino Sejdinovic, Heiko Strathmann, Massimiliano Pontil, Sivaraman Balakrishnan, Arthur Gretton, Optimal kernel choice for large-scale two-sample tests neural information processing systems. ,vol. 25, pp. 1205- 1213 ,(2012)
Sinno Jialin Pan, Ivor W. Tsang, James T. Kwok, Qiang Yang, Domain Adaptation via Transfer Component Analysis IEEE Transactions on Neural Networks. ,vol. 22, pp. 199- 210 ,(2011) , 10.1109/TNN.2010.2091281
Boqing Gong, Yuan Shi, Fei Sha, K. Grauman, Geodesic flow kernel for unsupervised domain adaptation computer vision and pattern recognition. pp. 2066- 2073 ,(2012) , 10.1109/CVPR.2012.6247911
Yoshua Bengio, Hod Lipson, Jeff Clune, Jason Yosinski, How transferable are features in deep neural networks neural information processing systems. ,vol. 27, pp. 3320- 3328 ,(2014)