I Tripled My YOLO Detection - Without Retraining

A quiet technique that lives between the model and your output: letting the scene decide what counts as a valid detection. (Credits to Gemini for generating this image) If you work with object detection in crowded spaces, like a classroom or an auditorium, you know the struggle. The students in the first three rows are detected perfectly with 0.85+ confidence. But Everyone further back? Ignored. Not because they weren’t there. Not because they were occluded. Just because they were small, and the model’s fixed confidence threshold was cutting them off.