
Radar Point Density Beats Architecture in Classification
An experiment on RadarScenes found that radar point density, rather than model architecture, was the main bottleneck for a five-class radar-only object classifier. Increasing points per instance from one to five nearly doubled macro F1 from 0.381 to 0.764, while architecture and feature changes remained within the measured noise floor.
Reddit r/MachineLearning · 9d ago






















