Subway Station Hazard Detection

This project is part of the CS course 'Systems Engineering Meets Life Sciences II' at Goethe University Frankfurt. In this Computer Vision project, we developed a first prototype of a security system which uses the surveillance cameras at subway stations to recognize dangerous situations. The training data was artificially generated by a Unity-based simulation.
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Python
C Sharp
Deep Learning
Machine Learning
Pytorch
Unity
Computer Vision
University
Blender
Semantic Segmentation
Surveillance