Anomaly detection method, anomaly detection device, anomaly detection program and learning method

摘要

PROBLEM TO BE SOLVED: To realize highly accurate abnormality detection while compensating for a shortage of teacher data. An abnormality detection method according to one aspect of the embodiment includes a generation step, a learning step, and a determination step. The generation step generates a learning data set containing a combination of a good product and a non-defective product as a positive example and a combination of a non-defective product and a defective product as a negative example in the same ratio based on the image data of the product. In the learning process, deep distance learning using the learning data set is performed to determine that the features of the positive example and the features of the negative example are embedded in the feature space while optimizing the distance between them. Output the model. In the judgment step, by inputting the judgment target image into the judgment model, the difference value between the feature amount of the judgment target image and the feature amount of the positive example is acquired from the judgment model, and the difference value in the judgment target image is obtained based on the difference value. Determine if the product is non-defective or defective. [Selection diagram] FIG. 2A