公开(公告)号：WO2018134290A1

公开(公告)日：2018-07-26

申请号：PCT/EP2018/051171

申请日：2018-01-18

Applicant: ASML NETHERLANDS B.V. ,  HERMES MICROVISION, INC.

Inventor： FANG, Wei ,  TEH, Cho ,  CHIEN, Ju, Hao ,  WANG, Yi-Ying ,  CHEN, Shih-Tsung ,  LIAO, Jian-Min ,  LI, Chuan ,  GUO, Zhaohui ,  HUANG, Pang-Hsuan ,  LAI, Shao-Wei ,  HSU, Shih-Tsung

IPC: G06T11/00

Abstract: A defect displaying method is provided in the disclosure. The method comprises acquiring defect group information from an image of a wafer, wherein the defect group information includes a set of correlations between a plurality of defects identified from the image and one or more corresponding assigned defect types and displaying at least some of the plurality of defects according to their corresponding assigned defect types.

公开(公告)号：WO2018134158A1

公开(公告)日：2018-07-26

申请号：PCT/EP2018/050903

申请日：2018-01-15

Applicant: ASML NETHERLANDS B.V. ,  HERMES MICROVISION, INC.

Inventor： FANG, Wei ,  TEH, Cho ,  JIAN, Robeter ,  WANG, Yi-Ying ,  CHEN, Shih-Tsung ,  LIAO, Jian-Min ,  LI, Chuan ,  GUO, Zhaohui ,  HUANG, Pang-Hsuan ,  LAI, Shao-Wei ,  HSU, Shih-Tsung

IPC: G05B19/418

Abstract: A server for knowledge recommendation for defect review. The server includes a processor electronically coupled to an electronic storage device storing a plurality of knowledge files related to wafer defects. The processor is configured to execute a set of instruction to cause the server to: receive a request for knowledge recommendation for inspecting an inspection image from a defect classification server; search for a knowledge file in the electronic storage device that matches the inspection image; and transmit the search result to the defect classification server.

公开(公告)号：WO2020011648A1

公开(公告)日：2020-01-16

申请号：PCT/EP2019/068015

申请日：2019-07-04

Applicant: ASML NETHERLANDS B.V.

Inventor： FANG, Wei ,  GUO, Zhaohui ,  ZHU, Ruoyu ,  LI, Chuan

IPC: G06T7/00

Abstract: A pattern grouping method may include receiving an image of a first pattern, generating a first fixed-dimensional feature vector using trained model parameters applying to the received image, and assigning the first fixed-dimensional feature vector a first bucket ID. The method may further include creating a new bucket ID for the first fixed-dimensional feature vector in response to determining that the first pattern does not belong to one of a plurality of buckets corresponding to defect patterns, or mapping the first fixed-dimensional feature vector to the first bucket ID in response to determining that the first pattern belongs to one of a plurality of buckets corresponding to defect patterns.