메뉴 건너뛰기




Volumn , Issue , 2007, Pages 587-591

Recognition of semiconductor defect patterns using spectral clustering

Author keywords

Data mining; Defect pattern; Fuzzy clustering; Spectral clustering

Indexed keywords

DATA MINING; DEFECTS; FUZZY CLUSTERING; PROBLEM SOLVING;

EID: 40649114008     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IEEM.2007.4419257     Document Type: Conference Paper
Times cited : (14)

References (22)
  • 2
    • 2342543476 scopus 로고    scopus 로고
    • Learning eigenfunctions of similarity: Linking spectral clustering and kernel PCA,
    • Technical Report, University de Montral
    • Y. Bengio, P. Vincent, and J. F. Paiement, "Learning eigenfunctions of similarity: linking spectral clustering and kernel PCA," Technical Report, University de Montral, 2003.
    • (2003)
    • Bengio, Y.1    Vincent, P.2    Paiement, J.F.3
  • 3
    • 0030326891 scopus 로고    scopus 로고
    • Regularized Gaussian discriminant analysis through eigenvalue decomposition
    • H. Bensmail and G. Celeux, "Regularized Gaussian discriminant analysis through eigenvalue decomposition," Journal of the American Statistical Association, vol. 91, pp. 1743-1748, 1996.
    • (1996) Journal of the American Statistical Association , vol.91 , pp. 1743-1748
    • Bensmail, H.1    Celeux, G.2
  • 5
    • 0034245675 scopus 로고    scopus 로고
    • A neural-network approach to recognize defect spatial pattern in semiconductor fabrication
    • F.L. Chen and S.F. Liu, "A neural-network approach to recognize defect spatial pattern in semiconductor fabrication," IEEE Transactions on Semiconductor Manufacturing, vol. 13, pp. 366-372, 2000.
    • (2000) IEEE Transactions on Semiconductor Manufacturing , vol.13 , pp. 366-372
    • Chen, F.L.1    Liu, S.F.2
  • 6
    • 33845660695 scopus 로고    scopus 로고
    • Data mining for yield enhancement in semiconductor manufacturing and an empirical study
    • C.F. Chien, W.C. Wang, and J.C. Cheng, "Data mining for yield enhancement in semiconductor manufacturing and an empirical study," Expert Systems with Applications, vol. 33, no. 1, pp. 192-198, 2007.
    • (2007) Expert Systems with Applications , vol.33 , Issue.1 , pp. 192-198
    • Chien, C.F.1    Wang, W.C.2    Cheng, J.C.3
  • 8
  • 10
    • 0036565280 scopus 로고    scopus 로고
    • Mercer kernel based clustering in the feature space
    • M. Girolami, "Mercer kernel based clustering in the feature space," IEEE Transactions on Neural Networks, vol. 13, no. 3, pp. 780-784, 2002.
    • (2002) IEEE Transactions on Neural Networks , vol.13 , Issue.3 , pp. 780-784
    • Girolami, M.1
  • 12
    • 0018057468 scopus 로고
    • Fuzzy clustering with a fuzzy covariance matrix
    • San Diego, pp
    • D. E. Gustafson and W. C. Kessel, "Fuzzy clustering with a fuzzy covariance matrix," Proc. IEEE-CDC, San Diego, pp. 761-766, 1979.
    • (1979) Proc. IEEE-CDC , pp. 761-766
    • Gustafson, D.E.1    Kessel, W.C.2
  • 13
    • 0031200533 scopus 로고    scopus 로고
    • Monitoring wafer map data from integrated circuit fabrication process for spatially clustered defects
    • M.H. Hansen, D.J. Friedman, and V.J. Nair, "Monitoring wafer map data from integrated circuit fabrication process for spatially clustered defects," Technometrics, vol. 39, no. 3, pp. 241-253, 1997.
    • (1997) Technometrics , vol.39 , Issue.3 , pp. 241-253
    • Hansen, M.H.1    Friedman, D.J.2    Nair, V.J.3
  • 14
    • 33750830235 scopus 로고    scopus 로고
    • Model-based clustering for integrated circuit yield enhancement
    • J.Y. Hwang and W. Kuo, "Model-based clustering for integrated circuit yield enhancement," European Journal of Operational Research, vol. 178, no. 1,pp. 143-153, 2007.
    • (2007) European Journal of Operational Research , vol.178 , Issue.1 , pp. 143-153
    • Hwang, J.Y.1    Kuo, W.2
  • 16
    • 10644261327 scopus 로고    scopus 로고
    • Evaluation of the performance of clustering algorithms in kernl-induced feature space
    • D.W. Kim, K.Y. Lee, D. Lee, and K.H. Lee, "Evaluation of the performance of clustering algorithms in kernl-induced feature space," Pattern Recognition, vol. 38, pp. 607-611, 2005.
    • (2005) Pattern Recognition , vol.38 , pp. 607-611
    • Kim, D.W.1    Lee, K.Y.2    Lee, D.3    Lee, K.H.4
  • 19
    • 26944437870 scopus 로고    scopus 로고
    • Possibilistic approach to kernel-based fuzzy c-means clustering with entropy regularization
    • K. Mizutani and S. Miyamoto, "Possibilistic approach to kernel-based fuzzy c-means clustering with entropy regularization," Lecture Notes in Computer Science, vol. 3558, pp. 144-155, 2005.
    • (2005) Lecture Notes in Computer Science , vol.3558 , pp. 144-155
    • Mizutani, K.1    Miyamoto, S.2
  • 21
    • 40649094289 scopus 로고    scopus 로고
    • Spectral clustering and kernel principal component analysis are pursuing good projections, Technical Report, University of Maryland, College Park
    • V.C. Raykar, "Spectral clustering and kernel principal component analysis are pursuing good projections," Technical Report, University of Maryland, College Park, 2004.
    • (2004)
    • Raykar, V.C.1
  • 22
    • 33750132385 scopus 로고    scopus 로고
    • Detection and classification of defect patterns on semiconductor wafers
    • C.H. Wang, W. Kuo, and H. Bensmail, "Detection and classification of defect patterns on semiconductor wafers," HE Transactions, vol. 38, pp. 1059-1068, 2006.
    • (2006) HE Transactions , vol.38 , pp. 1059-1068
    • Wang, C.H.1    Kuo, W.2    Bensmail, H.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.