Application of two Hopfield neural networks for automatic four-element LED inspection

IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews

Volumn 39, Issue 3, 2009, Pages 352-365

  Chang, Chuan Yu ^a   Li, Chun Hsi ^b   Lin, Si Yan ^a   Jeng, MuDer ^b  

^a NATIONAL YUNLIN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Taiwan)

^b NATIONAL TAIWAN OCEAN UNIVERSITY   (Taiwan)

Author keywords

Automatic optical inspection (AOI); Defect inspection; Four element LED; Hopfield neural networks

Indexed keywords

ALGAINP; ALUMINUM GALLIUM INDIUM PHOSPHIDES; AUTOMATIC INSPECTIONS; AUTOMATIC OPTICAL INSPECTION (AOI); DEFECT INSPECTION; FOUR-ELEMENT LED; PRODUCTION COSTS; SCANNING ELECTRON MICROSCOPES; WAFER IMAGES;

ALUMINA; DEFECTS; DIES; GALLIUM PHOSPHIDE; HOPFIELD NEURAL NETWORKS; INDIUM PHOSPHIDE; INSPECTION; OPTICAL TESTING; SCANNING ELECTRON MICROSCOPY;

NEURAL NETWORKS;

EID: 67349257006     PISSN: 10946977     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCC.2009.2013817     Document Type: Article

References (21)

1. C. T. Su, T. Yang, and C. M. Ke, "A neural-network approach for semiconductor wafer post-sawing inspection," IEEE Trans. Semicond. Manuf., vol. 15, no. 2, pp. 260-266, May 2002.
2. K. W. Tobin, Jr., T. P. Karnowski, and F. Lakhani, "Integrated applications of inspection data in the semiconductor manufacturing environment," SPIE, Metrol.-Based Control Micro-Manuf., vol. 4275, pp. 31-40, 2001.
3. D.P. Mital and E. K. Teoh, "Computer based wafer inspection system," in Proc. Int. Conf. Ind. Electron., Control Instrum., 1991, vol. 3, pp. 2497-2503.
4. J. M. Zhang, R. M. Lin, and M. J. Wang, "The development of an automatic post-sawing inspection system using computer vision techniques," Comput. Ind., vol. 40, no. 1, pp. 51430, Sep. 1999.
5. C.Y. Chang, "Contextual hopfield neural networks for medical image edge detection," Opt. Eng., vol. 45, no. 3, pp. 037006-037014, Mar. 2006.
6. P. C. Chung, C. T. Tsai, E. L. Chen, and Y. N. Sun, "Polygonal approximation using a competitive Hopfield neural network," Pattern Recognit., vol. 27, no. 11, pp. 1505-1512, Mar. 1994.
7. R. M. Haralick and L. G. Shapiro, Computer and Robot Vision, vol. I. Reading, MA: Addison-Wesley, 1992, pp. 28-48.
8. K. S. Cheng, J. S. Lin, and C. W. Mao, "The application of competitive Hopfield neural network to medical image segmentation," IEEE Trans. Med. Imaging, vol. 15, no. 4, pp. 560-567, Aug. 1996.
9. R. L. Hsu, A. M. Mohamed, and A. K. Jain, "Face detection in color image," IEEE Trans. Pattern Anal. Mach., vol. 24, no. 5, pp. 696-706, May 2002.
10. C.Y. Chang, H. J. Wang, and S. Y. Lin, "Simulation studies of two-layer Hopfield neural networks for automatic wafer defect inspection," Lecture Notes Comput. Sci., vol. 4031, pp. 1119-1126, 2006.
11. M. Maclure and W. C. Willett, "Misinterpretation and misuse of the kappa statistic," Am. J. Epidemiol., vol. 126, no. 2,, pp. 161-169, Aug. 1987.
12. M.J. Wang and C. L. Huang, "Evaluating the eye fatigue problem in wafer inspection," IEEE Trans. Semicond. Manuf., vol. 17, no. 3, pp. 444-447, Aug. 2004.
13. K. K. Chintalapudi and M. Kam, "A Noise-resistant fuzzy c-means algorithm for clustering," in Proc. IEEE Conf. Fuzzy Syst. Proc., 1998, vol. 2, pp. 1458-1463.
14. N. Otsu, "A threshold selection method from gray-scale histogram," IEEE Trans. Syst., Man, Cybern., vol. SMC-8, no. 1, pp. 62436, Jan. 1978.
15. H. K. Bhullar, P. Chia, K. Ong, and W. I. Ng, "Assessment of inter-observer and intra-observer variability in the measurement of QT dispersion," in Proc. Comput. Cardiol., 1996, pp. 297-300.
16. T. McGinn, P. C. Wyer, T. B. Newman, S. Keitz, R. Leipzig, and G. Guyatt for The Evidence-Based Medicine Teaching Tips Working Group, "Tips for learners of evidence-based medicine: 3. Measures of observer variability (kappa statistic)," Can. Med. Assoc. J., vol. 171, no. 11, pp. 1369-1373, Nov. 2004.
17. R. C. Gonzales and R. E. Woods, Digital Image Processing, 2nd ed. Upper Saddle River, NJ: Prentice-Hall, 2002, p. 1, pp. 124.
18. C. Y. Chang and P. C. Chung, "Two-layer competitive based Hopfield neural network for medical image edge detection," Opt. Eng., vol. 39, no. 3, pp. 695-703, Mar. 2000.
19. S. Haykin, Neural Networks, A Comprehensive Introduction, 2nd ed. Upper Saddle River, NJ: Prentice-Hall, 1999, pp. 682.
20. S. Wang and H. Wang, "Password authentication using Hopfield neural networks," IEEE Trans. Syst., Man, Cybern. C, Appl. Rev., vol. 38, no. 2, pp. 265-268, Mar. 2008.
21. S. Salcedo-Sanz, R. Santiago-Mozos, and C. Bousono-Calzon, "A hybrid Hopfield network-simulated annealing approach for frequency assignment in satellite communications systems," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 34, no. 2, pp. 1108-1116, Apr. 2004.