Unified neural network for defect detection and classification
First Claim
1. A system configured to detect and classify defects on a specimen, comprising:
- one or more computer subsystems; and
one or more components executed by the one or more computer subsystems, wherein the one or more components comprise;
a neural network configured for detecting defects on a specimen and classifying the defects detected on the specimen, wherein the neural network comprises;
a first portion configured for determining features of images of the specimen generated by an imaging subsystem; and
a second portion configured for detecting defects on the specimen based on the determined features of the images and classifying the defects detected on the specimen based on the determined features of the images, wherein the second portion comprises a proposal network configured for detecting defects on the specimen based on the features determined for the images, and wherein the proposal network detects the defects without classifying the defects; and
wherein the one or more computer subsystems are configured for generating results of the detecting and classifying.
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Accused Products
Abstract
Methods and systems for detecting and classifying defects on a specimen are provided. One system includes one or more components executed by one or more computer subsystems. The one or more components include a neural network configured for detecting defects on a specimen and classifying the defects detected on the specimen. The neural network includes a first portion configured for determining features of images of the specimen generated by an imaging subsystem. The neural network also includes a second portion configured for detecting defects on the specimen based on the determined features of the images and classifying the defects detected on the specimen based on the determined features of the images.
28 Citations
26 Claims
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1. A system configured to detect and classify defects on a specimen, comprising:
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one or more computer subsystems; and one or more components executed by the one or more computer subsystems, wherein the one or more components comprise; a neural network configured for detecting defects on a specimen and classifying the defects detected on the specimen, wherein the neural network comprises; a first portion configured for determining features of images of the specimen generated by an imaging subsystem; and a second portion configured for detecting defects on the specimen based on the determined features of the images and classifying the defects detected on the specimen based on the determined features of the images, wherein the second portion comprises a proposal network configured for detecting defects on the specimen based on the features determined for the images, and wherein the proposal network detects the defects without classifying the defects; and wherein the one or more computer subsystems are configured for generating results of the detecting and classifying. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23)
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24. A system configured to detect and classify defects on a specimen, comprising:
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an imaging subsystem configured for generating images of a specimen; one or more computer subsystems configured for acquiring the images; and one or more components executed by the one or more computer subsystems, wherein the one or more components comprise; a neural network configured for detecting defects on the specimen and classifying the defects detected on the specimen, wherein the neural network comprises; a first portion configured for determining features of the images of the specimen generated by the imaging subsystem; and a second portion configured for detecting defects on the specimen based on the determined features of the images and classifying the defects detected on the specimen based on the determined features of the images, wherein the second portion comprises a proposal network configured for detecting defects on the specimen based on the features determined for the images, and wherein the proposal network detects the defects without classifying the defects; and wherein the one or more computer subsystems are configured for generating results of the detecting and classifying.
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25. A non-transitory computer-readable medium, storing program instructions executable on one or more computer systems for performing a computer-implemented method for detecting and classifying defects on a specimen, wherein the computer-implemented method comprises:
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acquiring images of a specimen generated by an imaging subsystem; determining features of the images of the specimen by inputting the images into a first portion of a neural network configured for detecting defects on the specimen and classifying the defects detected on the specimen, wherein one or more components are executed by the one or more computer systems, and wherein the one or more components comprise the neural network; detecting defects on the specimen based on the determined features of the images and classifying the defects detected on the specimen based on the determined features of the images by inputting the determined features of the images into a second portion of the neural network, wherein the second portion comprises a proposal network configured for detecting defects on the specimen based on the features determined for the images, and wherein the proposal network detects the defects without classifying the defects; and generating results of the detecting and classifying.
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26. A computer-implemented method for detecting and classifying defects on a specimen, comprising:
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acquiring images of a specimen generated by an imaging subsystem; determining features of the images of the specimen by inputting the images into a first portion of a neural network configured for detecting defects on the specimen and classifying the defects detected on the specimen, wherein one or more components are executed by one or more computer systems, and wherein the one or more components comprise the neural network; detecting defects on the specimen based on the determined features of the images and classifying the defects detected on the specimen based on the determined features of the images by inputting the determined features of the images into a second portion of the neural network, wherein the second portion comprises a proposal network configured for detecting defects on the specimen based on the features determined for the images, and wherein the proposal network detects the defects without classifying the defects; and generating results of the detecting and classifying.
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Specification