US 12,230,013 B2
Fully automated SEM sampling system for e-beam image enhancement
Wentian Zhou, San Jose, CA (US); Liangjiang Yu, San Jose, CA (US); Teng Wang, San Jose, CA (US); Lingling Pu, San Jose, CA (US); and Wei Fang, San Jose, CA (US)
Assigned to ASML Netherlands B.V., Veldhoven (NL)
Filed by ASML Netherlands B.V., Veldhoven (NL)
Filed on Aug. 3, 2023, as Appl. No. 18/365,134.
Application 18/365,134 is a continuation of application No. 16/718,706, filed on Dec. 18, 2019, granted, now 11,769,317.
Claims priority of provisional application 62/787,031, filed on Dec. 31, 2018.
Prior Publication US 2024/0046620 A1, Feb. 8, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G06T 7/00 (2017.01); G06F 18/214 (2023.01); G06V 10/774 (2022.01); G06V 10/776 (2022.01); G06V 10/98 (2022.01)
CPC G06V 10/774 (2022.01) [G06F 18/214 (2023.01); G06T 7/0006 (2013.01); G06V 10/776 (2022.01); G06V 10/993 (2022.01); G06T 2207/10061 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30148 (2013.01)] 20 Claims
OG exemplary drawing
 
1. An electron beam inspection apparatus, comprising:
a memory; and
at least one processor coupled to the memory and configured to execute instructions to cause the electron beam inspection apparatus to perform operations comprising:
obtain an image acquired by a charged particle device; and
modify the obtained image using a machine learning model to generate a modified image, wherein the machine learning model was trained by:
analyzing a plurality of patterns of data relating to a layout of a product to identify a plurality of training locations to use to train the machine learning model;
obtaining a first image having a first quality for each of the plurality of training locations;
obtaining a second image having a second quality for each of the plurality of training locations, the second quality being higher than the first quality; and
using the first image and the second image to train the machine learning model.