Conceptual comparison between YOLO-based one-stage detectors (left) and DETR-based set-prediction detectors (right) for strong-lens searches. YOLO models generate dense predictions on a feature grid that are filtered by nonmaximum suppression (NMS), whereas DETR-style models decode a fixed set of object queries and output the final detections directly, without a separate postprocessing stage.