Non-transitory computer-readable medium and method for monitoring a semiconductor fabrication process

A method of converting an image of a semiconductor wafer to monitor a semiconductor fabrication process, the method comprising:

• receiving a first image and a second image of a semiconductor wafer by a processor executing an image conversion model having an artificial neural network;
• training the artificial neural network of the image conversion model by:
• inputting a dataset representing the first image and the second image;
• generating a conversion image of the semiconductor wafer based on the first image, the conversion image having a higher resolution than the first image;
• calibrating weights and biases of the artificial neural network to match the conversion image to the second image within a predetermined differential reference value;
• and
• generating a third image based on the calibrated weights and biases of the artificial neural network.

A system comprising:

• at least one processor;
• and
• at least one non-transitory computer-readable storage medium storing instructions that, when executed by the at least one processor, cause the system to:
• receive a first image and a second image of a semiconductor wafer, the first image and the second image being generated by a scanning electron microscope, wherein the second image has a higher resolution than the first image;
• train an artificial neural network of an image conversion model by:
• inputting a dataset representing the first image and the second image;
• generate a conversion image of the semiconductor wafer based on the first image, the conversion image having a higher resolution than the first image;
• calibrating weights and biases of the artificial neural network to match the conversion image to the second image within a predetermined differential reference value;
• and
• generating a third image of the semiconductor wafer based on the calibrated weights and biases of the artificial neural network.