公开(公告)号：US20230377125A1

公开(公告)日：2023-11-23

申请号：US17748996

申请日：2022-05-19

Applicant: Applied Materials Israel Ltd.

Inventor： Boaz DUDOVICH ,  Assaf ARIEL ,  Amir BAR ,  Lior YEHIELI ,  Chen ITZIKOWITZ ,  Shiran BEN ISRAEL ,  Lior KATZ ,  Eli Oren JONI ,  Eyal ROT

IPC: G06T7/00 ,  G06T3/00 ,  H04N7/01

CPC classification number: G06T7/001 ,  G06T3/0056 ,  H04N7/01 ,  G06T2207/20081 ,  G06T2207/30148

Abstract: There is provided a system and method of defect detection of a semiconductor specimen. The method includes obtaining a first image of the specimen acquired at a first bit depth, converting by a first processor the first image to a second image with a second bit depth lower than the first bit depth, transmitting the second image to a second processor configured to perform first defect detection on the second image using a first defect detection algorithm to obtain a first set of defect candidates, and sending locations of the first set of defect candidates to the first processor, extracting, from the first image, a set of image patches corresponding to the first set of defect candidates based on the locations, and performing second defect detection on the set of image patches using a second defect detection algorithm to obtain a second set of defect candidates.

公开(公告)号：US20230408423A1

公开(公告)日：2023-12-21

申请号：US17845953

申请日：2022-06-21

Applicant: Applied Materials Israel Ltd.

Inventor： Paz YABBO ,  Boaz DUDOVICH ,  Bhavna GHAI ,  Amir BAR

IPC: G01N21/95 ,  G06N3/08 ,  G06T7/00

CPC classification number: G01N21/9501 ,  G06N3/08 ,  G06T7/0004 ,  G06T2207/30148 ,  G06T2207/20081

Abstract: There is provided a system and method of optimizing an inspection recipe for inspecting a semiconductor specimen. The method includes obtaining test data from a test performed after inspection, the test data indicative of functional defectivity of the specimen with respect to at least one structural feature at a suspected layer; retrieving inspection data of the suspected layer including a set of inspection images and a set of defect maps of the plurality of processing steps of the suspected layer; correlating the test data and the set of defect maps of the suspected layer to identify one or more structural features of the suspected layer with unmatched defectivity; for each of the identified structural features, including at least part of the inspection images corresponding to the structural feature in a training set; and using the training set to train a machine learning (ML) model in the inspection recipe.