US Patent Issued to Synaptics on Dec. 23 for "Neural network training based on consistency loss" (California Inventor)

ALEXANDRIA, Va., Dec. 23 -- United States Patent no. 12,505,344, issued on Dec. 23, was assigned to Synaptics Inc. (San Jose, Calif.).

"Neural network training based on consistency loss" was invented by Omar Oreifej (Campbell, Calif.).

According to the abstract* released by the U.S. Patent & Trademark Office: "A system and method for denoising a sequence of images while maintaining a consistent appearance among images displayed consecutively in the sequence. A machine learning system maps a first input image in the sequence of images to a first output image based on a neural network algorithm and determines a first network loss based on differences between the first output image and a ground truth image. The system further maps a second i...