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This thesis investigates the issue of computer vision-based detection of oncoming cars during night-time, a critical road safety issue for automated high-beam assist. We propose a holistic image classification approach that uses deep learning methods to detect light artifacts from an oncoming car’s headlights before the car is entirely visible. We explore six different model architectures, includi
