August 11, 2020 | Tutorial, Deep Learning, HALCON

Deep-learning-based anomaly detection with MVTec HALCON

In this tutorial, you will learn how to train a deep-learning-based Anomaly Detection model for your own application.

First, we will take a look at the use cases and advantages of anomaly detection. Then we’ll go through the workflow step by step. We start with default preprocessing as well as with application-specific preprocessing. Afterward, the training parameters will be explained, and the trained model will be evaluated. Finally, we talk about the thresholds that define when a region or an image is classified as anomalous and visualize the inference results.

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Published on: August 11, 2020

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