In collaboration with XITASO, we have developed a trade fair showcase that presents object recognition and segmentation using neural networks. By using RGB and infrared cameras, road users such as cyclists and pedestrians are recognised under different environmental conditions. Pre-trained models such as YOLOv8 and Mask R-CNN are used, which have been subsequently fine-tuned to infrared data to enable reliable detection even in poor lighting conditions. →

Manufacturing industries must address the needs of their human resources to maintain efficiency and profitability in the global markets. By fostering safe, psychologically supportive working conditions, companies can improve work performance and retain their workforce in the face of labor shortage. →

Optimization of a reservoir channel by the civil engineering students of Augsburg Technical University →

A research project focused on identifying vulnerabilities in C and C++ code using Large Language Models. →

The mobile app for the Pyramid Company Contact Fair provides students and companies with a user-friendly platform for exchanging internships, projects, and jobs - anytime, anywhere. →

Augsburg car-free! The task is the integral planning of an above-ground modular parking system, which is at the same time an electricity power plant and offers co-working spaces. →

The project involves researching object recognition in image files and developing a concept for detecting objects in existing or self-generated datasets. →