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Performance Advancement of Evaluation Algorithm for Inner Defects in Semiconductor Packages  

Kim, Chang-Hyun (조선대학교 공과대학 메카트로닉스공학과)
Hong, Sung-Hun (조선대학교 공과대학 메카트로닉스공학과)
Kim, Jae-Yeol (전남대학교 전자컴퓨터공학부)
Publication Information
Transactions of the Korean Society of Machine Tool Engineers / v.15, no.6, 2006 , pp. 82-87 More about this Journal
Abstract
Availability of defect test algorithm that recognizes exact and standardized defect information in order to fundamentally resolve generated defects in industrial sites by giving artificial intelligence to SAT(Scanning Acoustic Tomograph), which previously depended on operator's decision, to find various defect information in a semiconductor package, to decide defect pattern, to reduce personal errors and then to standardize the test process was verified. In order to apply the algorithm to the lately emerging Neural Network theory, various weights were used to derive results for performance advancement plans of the defect test algorithm that promises excellent field applicability.
Keywords
Neural Network; Test Algorithm; Image Processing; Semiconductor Package; Performance Advancement;
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