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METHOD OF DEEP LEARINING-BASED EXAMINATION OF A SEMICONDUCTOR SPECIMEN AND SYSTEM THEREOF

机译:基于深度学习的半导体专业考试方法及其系统

摘要

There are provided system and method of segmentation a fabrication process (FP) image obtained in a fabrication of a semiconductor specimen. The method comprises: upon obtaining a Deep Neural Network (DNN) trained to provide segmentation-related data, processing a fabrication process (FP) sample using the obtained trained DNN and, resulting from the processing, obtaining by the computer segments-related data characterizing the FP image to be segmented, the obtained segments-related data usable for automated examination of the semiconductor specimen. The DNN is trained using a segmentation training set comprising a plurality of first training samples and ground truth data associated therewith, each first training sample comprises a training image; FP sample comprises the FP image to be segmented.
机译:提供了对在半导体样品的制造中获得的制造过程(FP)图像进行分割的系统和方法。该方法包括:在获得经过训练以提供与分段相关的数据的深度神经网络(DNN)之后,使用所获得的经过训练的DNN处理制造过程(FP)样本,并从该处理结果通过计算机获得与分段相关的数据表征对于要分割的FP图像,获得的与分割有关的数据可用于自动检查半导体样品。使用分割训练集来训练DNN,该分割训练集包括多个第一训练样本和与其相关联的地面真实数据,每个第一训练样本包括训练图像。 FP样本包括要分割的FP图像。

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