For real-world computer vision deployment, a two-stage pipeline with confidence-based abstention (refusing to predict when uncertain) is more reliable than forcing predictions—the model's uncertainty directly predicted where it would fail on new data.
Researchers built an open-source tool that automatically identifies vehicle types from roadway video to help understand cyclist safety in crashes. The system uses two AI models in sequence: first detecting vehicles in video frames, then classifying them into six specific body types (car, SUV, pickup truck, etc.).