基于神经网络的IC晶圆缺陷检测

Arsham Abedini, M. Ehsanian
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引用次数: 7

摘要

在许多研究中,使用参考图像来检测缺陷。但近年来,人们开始考虑无参考图像的缺陷检测。因为自动化视觉检测系统在工业发展中是必要的,特别是当工业中考虑到产品质量时[1]。因此,我们提出了一种基于缺陷特征的集成电路缺陷检测新方法。本文采用基于霍夫变换的缺陷离散度评价方法对缺陷进行分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Defect detection on IC wafers based on neural network
In many researches, defects are detected with using reference image. But recently, detection of defects without reference image is considered. Because Automated visual examination systems are necessary for developing in the industry, specifically when the quality of products is considered in industry [1]. Therefore, we present a novel method for detecting defects on integrated circuit based on defect features. In this paper, we classify defects with evaluating dispersion of defects based on Hough Transform.
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