Generating simulated images from input images for semiconductor applications
First Claim
1. A system configured to generate a simulated image from an input image, comprising:
- one or more computer subsystems configured to acquire an image for a specimen by directing energy to the specimen and detecting energy from the specimen using the specimen itself and imaging hardware; and
one or more components executed by the one or more computer subsystems, wherein the one or more components comprise;
a neural network, wherein the neural network comprises;
two or more encoder layers configured for determining features of the image for the specimen, wherein the image is a low resolution image of the specimen; and
two or more decoder layers configured for generating one or more simulated images from the determined features, wherein the one or more simulated images are one or more high resolution images of the specimen, wherein the neural network is configured as a deep generative model, and wherein the neural network does not comprise a fully connected layer thereby eliminating constraints on size of the image input to the two or more encoders layers.
1 Assignment
0 Petitions
Accused Products
Abstract
Methods and systems for generating a simulated image from an input image are provided. One system includes one or more computer subsystems and one or more components executed by the one or more computer subsystems. The one or more components include a neural network that includes two or more encoder layers configured for determining features of an image for a specimen. The neural network also includes two or more decoder layers configured for generating one or more simulated images from the determined features. The neural network does not include a fully connected layer thereby eliminating constraints on size of the image input to the two or more encoder layers.
-
Citations
27 Claims
-
1. A system configured to generate a simulated image from an input image, comprising:
-
one or more computer subsystems configured to acquire an image for a specimen by directing energy to the specimen and detecting energy from the specimen using the specimen itself and imaging hardware; and one or more components executed by the one or more computer subsystems, wherein the one or more components comprise; a neural network, wherein the neural network comprises; two or more encoder layers configured for determining features of the image for the specimen, wherein the image is a low resolution image of the specimen; and two or more decoder layers configured for generating one or more simulated images from the determined features, wherein the one or more simulated images are one or more high resolution images of the specimen, wherein the neural network is configured as a deep generative model, and wherein the neural network does not comprise a fully connected layer thereby eliminating constraints on size of the image input to the two or more encoders layers. - 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, 24)
-
-
25. A system configured to generate a simulated image from an input image, comprising:
-
an imaging subsystem configured for generating an image of a specimen by directing energy to the specimen and detecting energy from the specimen using the specimen itself and imaging hardware, wherein the image is a low resolution image of the specimen; one or more computer subsystems configured for acquiring the image; and one or more components executed by the one or more computer subsystems, wherein the one or more components comprise; a neural network, wherein the neural network comprises; two or more encoder layers configured for determining features of the image; and two or more decoder layers configured for generating one or more simulated images from the determined features, wherein the one or more simulated images are one or more high resolution images of the specimen, wherein the neural network is configured as a deep generative model, and wherein the neural network does not comprise a fully connected layer thereby eliminating constraints on size of the image input to the two or more encoder layers.
-
-
26. A non-transitory computer-readable medium, storing program instructions executable on one or more computer systems for performing a computer-implemented method for generating a simulated image from an input image, wherein the computer-implemented method comprises:
-
acquiring an image for a specimen by directing energy to the specimen and detecting energy from the specimen using the specimen itself and imaging hardware; determining features of the image for the specimen by inputting the image into two or more encoder layers of a neural network, wherein the image is a low resolution image of the specimen, wherein the neural network is configured as a deep generative model, and wherein the neural network does not comprise a fully connected layer thereby eliminating constraints on size of the image input to the two or more encoder layers; and generating one or more simulated images from the determined features, wherein the one or more simulated images are one or more high resolution images of the specimen, wherein generating the one or more simulated images is performed by two or more decoder layers of the neural network, wherein said acquiring, said determining, and said generating are performed by the one or more computer systems, 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.
-
-
27. A computer-implemented method for generating a simulated image from an input image, comprising:
-
acquiring an image for a specimen by directing energy to the specimen and detecting energy from the specimen using the specimen itself and imaging hardware; determining features of the image for the specimen by inputting the image into two or more encoder layers of a neural network, wherein the image is a low resolution image of the specimen, wherein the neural network is configured as a deep generative model, and wherein the neural network does not comprise a fully connected layer thereby eliminating constraints on size of the image input to the two or more encoder layers; and generating one or more simulated images from the determined features, wherein generating the one or more simulated images is performed by two or more decoder layers of the neural network, wherein the one or more simulated images are one or more high resolution images of the specimen, wherein said acquiring, said determining, and said generating are performed by one or more computer systems, 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.
-
Specification