公开(公告)号：WO2023280487A1

公开(公告)日：2023-01-12

申请号：PCT/EP2022/065032

申请日：2022-06-02

Applicant: ASML NETHERLANDS B.V.

Inventor： LIANG, Haoyi ,  CHEN, Zhichao ,  PU, Lingling ,  CHANG, Fang-Cheng ,  YU, Liangjiang ,  WANG, Zhe

IPC: G06T3/00 ,  G06T7/33

Abstract: An improved systems and methods for correcting distortion of an inspection image are disclosed. An improved method for correcting distortion of an inspection image comprises acquiring an inspection image, aligning a plurality of patches of the inspection image based on a reference image corresponding to the inspection image, evaluating, by a machine learning model, alignments between each patch of the plurality of patches and a corresponding patch of the reference image, determining local alignment results for the plurality of patches of the inspection image based on a reference image corresponding to the inspection image, determining an alignment model based on the local alignment results, and correcting a distortion of the inspection image based on the alignment model.

公开(公告)号：WO2022135938A1

公开(公告)日：2022-06-30

申请号：PCT/EP2021/084837

申请日：2021-12-08

Applicant: ASML NETHERLANDS B.V.

Inventor： WANG, Zhe ,  YU, Liangjiang ,  PU, Lingling

IPC: G06T7/00

Abstract: An improved systems and methods for generating a synthetic defect image are disclosed. An improved method for generating a synthetic defect image comprises acquiring a machine learning-based generator model; providing a defect-free inspection image and a defect attribute combination as inputs to the generator model; and generating by the generator model, based on the defect-free inspection image, a predicted synthetic defect image with a predicted defect that accords with the defect attribute combination.

公开(公告)号：WO2023280489A1

公开(公告)日：2023-01-12

申请号：PCT/EP2022/065219

申请日：2022-06-03

Applicant: ASML NETHERLANDS B.V.

Inventor： LIANG, Haoyi ,  CHEN, Yani ,  YANG, Ming-Yang ,  YANG, Yang ,  HUANG, Xiaoxia ,  CHEN, Zhichao ,  YU, Liangjiang ,  WANG, Zhe ,  PU, Lingling

IPC: G06T7/00 ,  H01L21/66

Abstract: Systems and methods for detecting a defect on a sample include receiving a first image and a second image associated with the first image; determining, using a clustering technique, N first feature descriptor(s) for L first pixel(s) in the first image and M second feature descriptor(s) for L second pixel(s) in the second image, wherein each of the L first pixel(s) is co-located with one of the L second pixel(s), and L, M, and N are positive integers; determining K mapping probability between a first feature descriptor of the N first feature descriptor(s) and each of K second feature descriptor(s) of the M second feature descriptor(s), wherein K is a positive integer; and providing an output for determining whether there is existence of an abnormal pixel representing a candidate defect on the sample based on a determination that one of the K mapping probability does not exceed a threshold value.