Generating high resolution images from low resolution images for semiconductor applications

A system configured to generate a high resolution image for a specimen from a low resolution image of the specimen, comprising:

• an imaging subsystem configured for generating a low resolution image of a specimen;
• one or more computer subsystems configured for acquiring the low resolution image of the specimen;
• and
• one or more components executed by the one or more computer subsystems, wherein the one or more components comprise:
• a deep convolutional neural network, wherein the deep convolutional neural network comprises:
• one or more first layers configured for generating a representation of the low resolution image;
• and
• one or more second layers configured for generating a high resolution image for the specimen from the representation of the low resolution image, wherein the one or more second layers comprise a final layer configured to output the high resolution image, and wherein the final layer is further configured as a sub-pixel convolution layer.

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 high resolution image for a specimen from a low resolution image of the specimen, wherein the computer-implemented method comprises:

• acquiring a low resolution image of a specimen;
• generating a representation of the low resolution image by inputting the low resolution image into one or more first layers of a deep convolutional neural network;
• and
• generating a high resolution image for the specimen based on the representation, wherein generating the high resolution image is performed by one or more second layers of the deep convolutional neural network, wherein the one or more second layers comprise a final layer configured to output the high resolution image, wherein the final layer is further configured as a sub-pixel convolution layer, wherein said acquiring, said generating the representation, and said generating the high resolution image 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 deep convolutional neural network.

A computer-implemented method for generating a high resolution image for a specimen from a low resolution image of the specimen, comprising:

• acquiring a low resolution image of a specimen;
• generating a representation of the low resolution image by inputting the low resolution image into one or more first layers of a deep convolutional neural network;
• and
• generating a high resolution image for the specimen based on the representation, wherein generating the high resolution image is performed by one or more second layers of the deep convolutional neural network, wherein the one or more second layers comprise a final layer configured to output the high resolution image, wherein the final layer is further configured as a sub-pixel convolution layer, wherein said acquiring, said generating the representation, and said generating the high resolution image 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 deep convolutional neural network.