Paper Title:
The Performance Advancement of Test Algorithm Using Neural Network for Semiconductor Packages
  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.

  Info
Periodical
Key Engineering Materials (Volumes 261-263)
Edited by
Kikuo Kishimoto, Masanori Kikuchi, Tetsuo Shoji and Masumi Saka
Pages
411-416
DOI
10.4028/www.scientific.net/KEM.261-263.411
Citation
J. Y. Kim, J. K. Sim, M.J. Song, C. H. Kim, L. K. Kwac, "The Performance Advancement of Test Algorithm Using Neural Network for Semiconductor Packages", Key Engineering Materials, Vols. 261-263, pp. 411-416, 2004
Online since
April 2004
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Price
$32.00
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