The method of performance advancement using modified neural network for test algorithm of semiconductor packages

Abstract

The classification of defects in semiconductor packages was performed by the pattern recognition technology with modified neural network is based on image processing. The pattern recognition algorithm is composed of image processing and modified backpropagation neural network. Image processing is preprocessing method for dimensionality reduction that is input data of backpropagation neural network. And image processing is simply made of image equalization and binary image conversion and edge detection for reducing operation time. And most of algorithm of backpropagation neural network is generally used uniform train weight, but the algorithm in this research is applied to variously subdivided train weights of backpropagation neural network based on types of semiconductor packages according to kinds of defects. Through above processes, we obtained advanced result of pattern recognition about defects in semiconductor packages.