Samsung Electronics Co., Ltd.

Chan Young Hwang

Tae Ho Lee

Chang Wook Jeong

Jeongjin Lee

Seungyoon Lee

Minseok Kang

In Huh

Min Chul Park

An overlay correcting method capable of optimizing correction of an overlay within a scanner correction limit of a scanner of a scanner system, and a photolithography method, a semiconductor device manufacturing method and the scanner system which are based on the overlay correcting method are provided. The overlay correcting method includes collecting overlay data by measuring an overlay of a pattern; calculating correction parameters of the overlay by performing regularized regression using the overlay data, the regularized regression being based on a correction limit of the scanner such that the correction parameters fall within the correction limit of the scanner; and providing the correction parameters to the scanner.

Overlay correcting method, and photolithography method, semiconductor device manufacturing method and scanner system based on the overlay correcting method

A method for detecting defects in a semiconductor device includes pre-training a pre-trained convolutional neural network (CNN) model using a sampled clean data set extracted from a first data set; training a normal convolutional neural network model and a label-noise convolutional neural network model using first data of the first data set and the pre-trained convolutional neural network model. The method also includes outputting a first prediction result on whether second data of a second data set is good or bad using the second data and the normal convolutional neural network model; and outputting a second prediction result on whether second data is good or bad using the second data and the label-noise convolutional neural network model. The first prediction result is compared with the second prediction result to perform noise correction when there is a label difference. Third data created as results of the noise correction is added to the sampled clean data set. The normal convolutional neural network model and the label-noise convolutional neural network model are additionally using the sampled clean data set with the third data added.

Method for detecting defects in semiconductor device

Growing community of inventors

Asan-si, South Korea

Chan Young Hwang