Deep Learning in Machine Vision: Benefits and Application Examples

In machine vision, deep learning enables an increasing number of applications that were not possible before. Moreover, the performance of existing applications can also be significantly improved. Many industries are already benefiting from these new opportunities, such as machinery, food, recycling, logistics, etc. In this presentation, the audience will learn about some specific applications where deep learning has already been successfully implemented and what technology has been applied. Based on real application examples, the challenges are described and the added value of deep learning for these specific cases is highlighted.

About the presenter
In his capacity as the technical product manager at MVTec Software GmbH, Mario Bohnacker has been responsible for the technical enhancement of the standard machine vision software HALCON. His duties include identifying technologies that are relevant for future developments, as well as for customers, and turning the technologies into product innovations. He also directs the further development of HALCON to deliver maximum customer benefits.

Bohnacker began his career at MVTec in early 2017. As team leader solutions, he was responsible for all service business relating to customer projects, as well as training programs for the software products HALCON and MERLIC. Before joining MVTec, he worked from 2010 to 2014 for an international mechanical engineering company as a developer of machine vision software. Following that position, he headed the establishment of a machine vision development team for the company's Chinese subsidiary.