In the last videos, we learned how to prepare our data and perform the training of a deep-learning-based classifier with MVTec HALCON. In this video, we check out different methods that can help you evaluate this trained classifier, like confusion matrices and heatmaps. Furthermore, we use a procedure that can display, for example, all falsely classifier images, which can help you evaluate limitations of your classifier. Lastly, different evaluation measures can be computed, like the F-score, the Top-K-erro
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