Real-time Detection of Encoded Shapes with Deep Learning

Michelle Xiao-Lin Foo has received the Bosch Price for the best graduation from the faculty Mechatronic Summer Semester 2018 at the Reutlingen University.

Her graduation work was about “Real-time Detection of Encoded Shapes with Deep Learning”

With the rapid development of artificial intelligence, especially deep learning, computers are now able to interpret images close to human capabilities. One of the most important applications of deep learning is in the field of image understanding for autonomous vehicles. In this work, a shape prediction network was trained that generates near-real-time shape segmentation of detected objects.


How do I feel about the prize?

Michelle: I am very happy about it and I would like to thank my supervisors, professors, my family and friends for their unfailing support and guidance along the way.

Michelle is a Member of the RT Lions and the head of RT Lions Prof. Dr. Matthias Rätsch was also her supervisor for her graduation work. She was responsible for the implementation of object recognition module with CNN at the RoboCup 2017 in Nagoya and the RoboCup German Open 2017 in Magdeburg.

We are very happy to have Michelle in our Team and wish her the best for her future.