Ruiyu Zeng

This thesis aims to detect and classify lane markings in aerial images by using Python, Computer Vision (OpenCV) and deep learning. 1. Detection of lane markings and symbols in aerial images above highways and cities. 2. Classification of the lane markings and symbols into different categories. 3. Comparison the results between classical image processing and deep learning methods. 4. Develop and optimization of a algorithm combining classical methods with deep learning to complete the tasks.

Internship in Team Measurement Engineering, Department Overall Vehicle. Mainly focusing on: - Design and configuration of measurement system based on specific test requirements. - Provide measurement support for different testing projects. i.e. Autonomous Driving, Powertrain Testing, Engine Calibration and so on. - Implementation and installation of measurement system on vehicle. - Management, maintenance and regular calibration of more than 1500 pieces of measurement equipment and materials.

zwei Projektarbeit am Institute WZL; Masterarbeit am Institute von Fahrzeugtechnik