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The Development of Pattern Classification for Inner Defects in Semiconductor Packages by Self-Organizing Map  

김재열 (조선대학교 기계공학부)
윤성운 (조선대학교 기계공학부)
김훈조 (광주인력개발원 기계설계제작과)
김창현 (조선대하교 대학원 정밀기계공학과)
양동조 (조선대학교 대학원 정밀기계공학과)
송경석 (조선대학교 대학원 광응용공학과)
Publication Information
Transactions of the Korean Society of Machine Tool Engineers / v.12, no.2, 2003 , pp. 65-70 More about this Journal
Abstract
In this study, researchers developed the estimative algorithm for artificial defect in semiconductor packages and performed it by pattern recognition technology. For this purpose, the estimative algorithm was included that researchers made software with MATLAB. The software consists of some procedures including ultrasonic image acquisition, equalization filtering, Self-Organizing Map and Backpropagation Neural Network. Self-organizing Map and Backpropagation Neural Network are belong to methods of Neural Networks. And the pattern recognition technology has applied to classify three kinds of detective patterns in semiconductor packages : Crack, Delamination and Normal. According to the results, we were confirmed that estimative algerian was provided the recognition rates of 75.7% (for Crack) and 83.4% (for Delamination) and 87.2 % (for Normal).
Keywords
Pattern Classification; Inner Defects; Semiconductor Packages; Self-Organizing Map; Neural Network;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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