US Patent Issued to FANUC on Oct. 21 for "Threshold and model adaptation for the kNN-based anomaly detection method" (California Inventors)

ALEXANDRIA, Va., Oct. 28 -- United States Patent no. 12,450,729, issued on Oct. 21, was assigned to FANUC Corp. (Yamanashi, Japan).

"Threshold and model adaptation for the kNN-based anomaly detection method" was invented by Yujiao Cheng (Fremont, Calif.) and Tetsuaki Kato (Fremont, Calif.).

According to the abstract* released by the U.S. Patent & Trademark Office: "A method for anomaly detection from object images. A feature extractor provides feature data characterizing part images, including good parts and bad parts. Training data for good parts is used to create a k-nearest neighbors (k-NN) model core set. Adaptation data for some good and some bad parts is evaluated by a k-NN module to determine an anomaly score from the feature data....