Released the desktop application for unsupervised anomaly detection of sensor images, "Sensor AD."
We have started offering a desktop application called "Sensor AD" that learns the "normal standard" only from good product images and detects images that deviate from this standard as anomalies. There is no need to prepare a large number of defective product samples, allowing for the implementation of anomaly detection operations from the initial stages even in environments where collecting defective products is difficult. The inference runs on the CPU, and a GPU is not required. It features visualization through contribution heatmaps and automatic clustering of false positives.

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