Samsung patents AI method to speed up scanning electron microscope analysis
Samsung has been granted a patent for a system that uses a neural network to analyze images from scanning electron microscopes. The device breaks large images into smaller sections, uses AI to identify specific objects in each part, and then stitches the results back together to create a complete map of the target objects.
In the filing’s own words
A neural network device includes: (1) a pre-processor configured to select target images from scanning electron microscope (SEM) images, based on frequencies respectively corresponding to the SEM images, and crop each of the target images into a plurality of cropped images; (2) a neural network processor configured to generate a crop detection image by inferring a target object from each of the plurality of cropped images by using a segmentation model trained to detect the target object in each of the plurality of cropped images; and (3) a post-processor configured to merge crop detection images with each other in a same size as the SEM images, based on position information of the plurality of cropped images.
What exactly they claim (claim 1)
1. A neural network device comprising: a pre-processor configured to; convert time domain information of each scanning electron microscope (SEM) image of SEM images into frequency domain information, generate, from the frequency domain information, a frequency image corresponding to each of the SEM images, select target images from the SEM images based on a frequency value of at least a portion of each of the frequency images corresponding to the SEM images, set at least another portion of each of the frequency images as a zero-padding area by substituting zero for frequency values respectively corresponding to pixels of the at least another portion of the frequency image, wherein the zero-padding area is set based on a center of the frequency image, and crop each of the target images into a plurality of cropped images; a neural network processor configured to generate crop detection images by inferring a target object from each of the plurality of cropped images by using a segmentation model trained to detect the target object in each of the plurality of cropped images; and a post-processor configured to merge the crop detection images with each other to generate a merged image having the same size as the SEM images, based on position information of the plurality of cropped images.
Facts
- Company
- Samsung (SAMSUNG ELECTRONICS CO., LTD.)
- Official title
- Scanning electron microscope image processing using neural network
- Patent number
- US12738013B2
- Application number
- 18233385
- Filed
- Aug 14, 2023
- Granted
- Sep 15, 2026
- Inventors
- 6
- Claims
- 14
Classified under
G06V 10/26 Physics & computingG06T 5/50 Physics & computingG06T 7/11 Physics & computingG06V 10/774 Physics & computingG06V 10/82 Physics & computingG06T 2207/10061 Physics & computingMore from Samsung in AI & software
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Summaries are simplified from the filing’s own abstract and first claim. A patent filing is not a product announcement.
Patent data and drawings: U.S. Patent and Trademark Office (USPTO). Nebula is not affiliated with or endorsed by the USPTO.