György Katona successfully defended his Master's Thesis

György did his thesis on "Component Extraction from Scientific Publications using Convolutional Neural Networks". Congratulations!

In his thesis, he introduced a system capable of extracting components from scientific publications and a document annotation tool that makes the labeling process more than four times faster than other alternatives.

In the future, György would like to use his knowledge and experience to contribute to a safe and robust solution for autonomous vehicles. He therefore joined an international project that works on Level 4 self-driving vehicles.