公开(公告)号：US20200090304A1

公开(公告)日：2020-03-19

申请号：US16402375

申请日：2019-05-03

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： CHOONSIK LEEM ,  Taelim CHOI ,  Yongdeok KIM

IPC: G06T3/40 ,  G06T7/00

Abstract: A non-transitory computer-readable medium for monitoring a semiconductor fabrication process includes an image conversion model having an artificial neural network. The image conversion model, when executed, causes the processor to receive a first image and a second image of a semiconductor wafer. The artificial neural network is trained by inputting a dataset representing the first image and the second image, generating a conversion image of the semiconductor wafer and calibrating weights and biases of the artificial neural network to match the conversion image to the second image. A third image of the semiconductor wafer is generated based on the calibrated weights and biases of the artificial neural network. The image conversion model with the trained artificial neural network may be transmitted to another device for image conversion of low resolution images.

公开(公告)号：US20230054159A1

公开(公告)日：2023-02-23

申请号：US17748241

申请日：2022-05-19

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Taelim CHOI ,  Jun Haeng LEE

IPC: G05B19/418

Abstract: A method and device for predicting a defect. The method includes determining a sequence between a plurality of sub-models by modeling a production process into the plurality of sub-models, mapping production process data into each of the plurality of sub-models, determining, by a corresponding sub-model, output data comprising defect information on a potential defect occurring in a corresponding step, for each of the plurality of sub-models, predicting information associated with a defect in the production process based on the output data corresponding to each of the plurality of sub-models, and inputting the output data of each of the sub-models to a subsequent sub-model of the corresponding sub-model, based on the sequence.