Analyzing 2D Object Detection in Automated Driving Systems
The author introduces a novel introspection solution for error detection in 2D object detection systems, outperforming state-of-the-art methods by reducing missed error ratios. The approach leverages neural activation patterns to enhance error detection capabilities.
