Samsung electronics co., ltd. (20240320816). TRAINING SCANNING ELECTRON MICROSCOPY IMAGE SELECTION METHOD AND SEM EQUIPMENT ALIGNMENT METHOD USING THE SAME simplified abstract
TRAINING SCANNING ELECTRON MICROSCOPY IMAGE SELECTION METHOD AND SEM EQUIPMENT ALIGNMENT METHOD USING THE SAME
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TRAINING SCANNING ELECTRON MICROSCOPY IMAGE SELECTION METHOD AND SEM EQUIPMENT ALIGNMENT METHOD USING THE SAME - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240320816 titled 'TRAINING SCANNING ELECTRON MICROSCOPY IMAGE SELECTION METHOD AND SEM EQUIPMENT ALIGNMENT METHOD USING THE SAME
The patent application describes a method for selecting training scanning electron microscope (SEM) images by setting patterns as samples, training on these patterns to create a conversion model, converting the patterns into design patterns, comparing them with design images to identify misalignments, determining effective distances for each pattern, selecting the optimal training pattern with the maximum effective distance, and deleting samples within that distance.
- Setting patterns of SEM images as samples
- Training on patterns to generate a conversion model
- Converting patterns into design patterns
- Comparing converted design patterns with design images to detect misalignments
- Determining effective distances for each pattern
- Selecting optimal training pattern with maximum effective distance
- Deleting samples within maximum effective distance
- Determining alignment of all samples
Potential Applications: - Quality control in semiconductor manufacturing - Material analysis in research laboratories - Forensic analysis in criminal investigations
Problems Solved: - Efficient selection of SEM images for training - Improved accuracy in image alignment - Streamlined image analysis process
Benefits: - Enhanced image processing capabilities - Increased productivity in image analysis - Higher accuracy in pattern recognition
Commercial Applications: Title: "Advanced Image Selection Method for SEM Training" This technology can be used in semiconductor manufacturing, materials research, and forensic analysis industries to improve image analysis accuracy and efficiency.
Questions about the technology: 1. How does this method improve the efficiency of selecting SEM images for training? 2. What are the potential implications of misaligned patterns in SEM image analysis?
Frequently Updated Research: Stay updated on the latest advancements in SEM image analysis techniques and applications to enhance the efficiency and accuracy of image processing in various industries.
Original Abstract Submitted
a training scanning electron microscope (sem) image selection method includes setting a plurality of patterns of sem images as samples, performing training on a plurality of training patterns, respectively, to generate a conversion model, converting the training patterns into a plurality of converted design patterns by using the conversion model, comparing the plurality of converted design patterns with the corresponding design image pattern to determine misalignment therebetween, obtaining, for each of the plurality of training patterns, effective distances which are smallest values of distances from each of the plurality of training patterns to a pattern that is misaligned, extracting the training pattern having a maximum effective distance as an optimal training pattern, deleting the samples that are within the maximum effective distance in the optimal training pattern, and determining whether all the samples are aligned.
