公开(公告)号：US11151707B2

公开(公告)日：2021-10-19

申请号：US16277769

申请日：2019-02-15

Applicant: KLA-Tencor Corporation

Inventor： Santosh Bhattacharyya ,  Jacob George ,  Saravanan Paramasivam ,  Martin Plihal

IPC: G06T7/00 ,  G06N3/08 ,  G06N3/04 ,  G06K9/62 ,  G01N23/2251

Abstract: A system for defect review and classification is disclosed. The system may include a controller, wherein the controller may be configured to receive one or more training images of a specimen. The one or more training images including a plurality of training defects. The controller may be further configured to apply a plurality of difference filters to the one or more training images, and receive a signal indicative of a classification of a difference filter effectiveness metric for at least a portion of the plurality of difference filters. The controller may be further configured to generate a deep learning network classifier based on the received classification and the attributes of the plurality of training defects. The controller may be further configured to extract convolution layer filters of the deep learning network classifier, and generate one or more difference filter recipes based on the extracted convolution layer filters.

公开(公告)号：US20200184628A1

公开(公告)日：2020-06-11

申请号：US16277769

申请日：2019-02-15

Applicant: KLA-Tencor Corporation

Inventor： Santosh Bhattacharyya ,  Jacob George ,  Saravanan Paramasivam ,  Martin Plihal

IPC: G06T7/00 ,  G06N3/08 ,  G06N3/04 ,  G06K9/62 ,  G01N23/2251

Abstract: A system for defect review and classification is disclosed. The system may include a controller, wherein the controller may be configured to receive one or more training images of a specimen. The one or more training images including a plurality of training defects. The controller may be further configured to apply a plurality of difference filters to the one or more training images, and receive a signal indicative of a classification of a difference filter effectiveness metric for at least a portion of the plurality of difference filters. The controller may be further configured to generate a deep learning network classifier based on the received classification and the attributes of the plurality of training defects. The controller may be further configured to extract convolution layer filters of the deep learning network classifier, and generate one or more difference filter recipes based on the extracted convolution layer filters.