mvtec academy

Advanced trainings

Deepen your knowledge of MVTec software and technologies in our advanced trainings. 

Generic Shape Matching

This advanced training covers HALCON's shape-based matching along with its generic shape matching operator set. You will learn the benefits of shape matching, how to apply shape matching to your use case, and how to parameterize the most common parameters for optimal matching results.

Target Group

This training is aimed at advanced HALCON users who want to use the shape matching technology for their applications.


Upon completion of this course, you will:

  • gain an understanding of what 'matching' is in the context of machine vision and where shape matching can benefit your application.
  • get to know the workflow of generic shape matching.
  • understand the most important parameters, that affect robustness and runtime.
  • learn how to further process the shape matching results.
  • be able to solve your first basic shape matching applications.

Surface-Based Matching

This advanced training introduces you how to work with 3D Surface Matching. You learn the basics of 3D Surface Matching, the whole workflow of it, and details that improve the performance.

Target Group

This training is aimed at advanced HALCON users who has already attended course "Introduction to 3D", and who wants to do 3D object localization.


After finishing this course, you will …

  • know what Surface-Based Matching is,
  • know the workflow of Surface-Based Matching in HALCON and understand what each step does,
  • be able to debug the Surface-Based Matching results,
  • be able to improve the Surface-Based Matching regarding speed, robustness and accuracy.

Datasets for Deep Learning

Data is crucial for any deep learning application. In fact, even the most sophisticated Deep Learning model does not help you at all without suitable data.

This advanced training will teach you what to look out for and what to avoid when curating your Deep Learning dataset.

Target Group

This training is aimed at new and intermediate/advanced Deep Learning users who want to find out more about the importance of data in Deep Learning applications. Completing the “Introduction to Deep Learning” course is a prerequisite.


Upon completion of this course, you will …

  • understand why data is so important for any deep learning application.
  • be able to properly and accurately define the problem you want to solve with deep learning.
  • be able to assess the quality of your dataset.
  • know the requirements on datasets for the different deep learning methods.
  • be able to curate your own dataset and expertly evaluate the quality.