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'Towards Total Recall in Industrial Anomaly Detection
I understand that the paper officially embeds only the normal image and then determines the threshold using the standard deviation.
There is something I learned when I used the anomalib library. If there is a normal image or abnormal image, it seems that the normal image is embedded in training, and when valid, it is set to a threshold with the best F1 Score based on the normal image and abnormal image
This means that Patchcore is basically Unsupervisored Learning, but can it be considered as Supervisored Learning as it is used?
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'Towards Total Recall in Industrial Anomaly Detection
I understand that the paper officially embeds only the normal image and then determines the threshold using the standard deviation.
There is something I learned when I used the anomalib library. If there is a normal image or abnormal image, it seems that the normal image is embedded in training, and when valid, it is set to a threshold with the best F1 Score based on the normal image and abnormal image
This means that Patchcore is basically Unsupervisored Learning, but can it be considered as Supervisored Learning as it is used?
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