US 12,299,848 B2
Deep learning image denoising for semiconductor-based applications
Aditya Gulati, Chandigarh (IN); Raghavan Konuru, Andhra Pradesh (IN); Niveditha Lakshmi Narasimhan, Chennai (IN); Saravanan Paramasivam, Chennai (IN); Martin Plihal, Pleasanton, CA (US); and Prasanti Uppaluri, Saratoga, CA (US)
Assigned to KLA Corporation, Milpitas, CA (US)
Filed by KLA Corporation, Milpitas, CA (US)
Filed on Apr. 14, 2022, as Appl. No. 17/721,300.
Claims priority of provisional application 63/223,976, filed on Jul. 21, 2021.
Claims priority of application No. 202141024096 (IN), filed on May 31, 2021.
Prior Publication US 2022/0383456 A1, Dec. 1, 2022
Int. Cl. G06T 5/70 (2024.01); G06T 5/50 (2006.01); G06T 7/00 (2017.01)
CPC G06T 5/70 (2024.01) [G06T 5/50 (2013.01); G06T 7/001 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/20224 (2013.01); G06T 2207/30148 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A system configured to determine information for a specimen, comprising:
a computer subsystem; and
one or more components executed by the computer subsystem;
wherein the one or more components comprise a deep learning model configured for denoising an image of a specimen generated by an imaging subsystem; and
wherein the computer subsystem is configured for determining information for the specimen from the denoised image, wherein a defect is detected in the image or the denoised image, and wherein determining the information for the specimen comprises determining only a first portion of attributes of the defect from the denoised image, determining only a second portion of the attributes of the defect from the image, and determining information for the defect from the first and second portions of the attributes.