Optical high-resolution image-based defect inspection on compound semiconductors

Thomas Trautzsch, A. Mapelli, Timm Berndorfer, Christian Czogalla, Christoph Pfuhl
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Abstract

With the increase in volume and demand for smaller, faster, and more power-efficient integrated circuits, compound semiconductors have gained significant importance over silicon. In this paper, the authors intend to describe a novel implemented solution based on high-resolution images obtained with an automated optical inspection (AOI) system, combined with an artificial intelligence-based approach to identify, and classify defects for the purpose of a stable monitoring of the processing of compound semiconductors.
基于光学高分辨率图像的化合物半导体缺陷检测
随着体积的增加和对更小、更快、更节能集成电路的需求的增加,化合物半导体已经比硅获得了显著的重要性。在本文中,作者打算描述一种新的实现解决方案,该解决方案基于自动光学检测(AOI)系统获得的高分辨率图像,结合基于人工智能的方法来识别和分类缺陷,以稳定监测化合物半导体的加工过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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