<ul><li>Non-Maximum Suppression (NMS) is a technique used in object detection to eliminate redundant bounding box predictions.</li><li>Object detection models often produce multiple overlapping boxes with different positions and scores.</li><li>NMS ensures that only the highest-quality predictions remain by removing overlapping boxes that likely refer to the same object.</li><li>NMS is crucial for improving the quality of object detection outputs and is beneficial for downstream applications such as tracking and classification.</li></ul>

Non-Maximum Suppression for Object Detection

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