M.Sc.
Christian
Creß
Technische Universität München
Informatik 6 - Lehrstuhl für Robotik, Künstliche Intelligenz und Echtzeitsysteme (Prof. Knoll)
Postadresse
Boltzmannstr. 3
85748 Garching b. München
Dienstort
Informatik 6 - Lehrstuhl für Robotik, Künstliche Intelligenz und Echtzeitsysteme (Prof. Knoll)
Schleißheimerstraße 90a(8111)
85748 Garching b. München
Curriculum Vitae
Christian Creß joined the Chair of Robotics, Artificial Intelligence and Real-time Systems at the Technical University of Munich (TUM) in 2020 as Research Assistant and Ph.D. candidate under the supervison of Prof. Dr.-Ing. habil. Alois Christian Knoll. He completed his M.Sc. in Applied Computer Science at the University of Applied Sciences Kempten in 2016. His Master Thesis “Visual Scene Analysis for the Segmentation of Static and Dynamic Objects” was realized in collaboration with ESG Elektroniksystem- und Logistik-GmbH. Before starting as Research Assistant at TUM, he worked as software developer in the industry.
As a Research Assistant, he worked on the prestigious AUTOtech.agil and Providentia++ projects. Based on the innovative Providentia++ roadside intelligent transportation system, he is finishing his Ph.D. in the field of computer vision with event-based cameras, where he established the complete perception pipeline from calibration, object detection, and data fusion.
e-Mail: christian.cress [at] tum.de
LinkedIn
XING
Research Interests
- Computer Vision
- Artificial Intelligence
- Software Architecture
Completed and Ongoing Theses:
| Title | Author | Status | Type |
| Radar-based Instance Segmentation of Moving Objects using Machine Learning | Bengisu Ayan | Submitted 12/23 | Master Thesis |
| Camera-Based Object Detection in Poor-Visibility Conditions Using Adaptive Teacher | Zafercan Aygürler | Submitted 04/23 | Master Thesis |
| Deep Learning Based Rain Removal for Object Detection in Poor-Visibility-Scenes | Daniel Lehmberg | Submitted 02/23 | Bachelor Thesis |
| Runtime Calibration between Camera and Event-Based Camera for Sensor Fusion | Erik Schütz | Submitted 01/23 | Master Thesis |
| Synthetic Data Generation Using GANs for Camera Based Object Detection | Taiba Basit | Submitted 01/23 | Master Thesis |
| Object Detection in Poor-Visibility-Scenes Using Dynamic Adjustment of Pipeline Parameters | Can Bayraktaroglu | Submitted 10/22 | Master Thesis |
| Deep Learning Based Object Detection with Artificial Training Data for Poor-Visibility-Scenes | Xuemei Zhang | Submitted 08/22 | Bachelor Thesis |
| Accident Prevention Backend Framework to Support Autonomous Driving | Noir Nigmatov | Submitted 05/22 | Master Thesis |
| Accident Prevention Frontend Framework to Support Autonomous Driving | Mohammad Naanaa | Submitted 03/22 | Bachelor Thesis |
| Traffic Trajectory Prediction Within the Providentia++ Test Stretch | Jurek Olden | Submitted 05/22 | Master Thesis |
| Enhancing Robustness of Intelligent Transportation Systems Through Self-Diagnosis Functionality | Lukas Rabe | Submitted 06/21 | Master Thesis |
