Enhancing Object Detection via Refined Anchor Boxes and NMS
Boosting Object Detection Accuracy: NMS and Refined Anchors Object detection, the ability of a computer to identify and locate objects within an image, is a fundamental task in computer vision with applications ranging from self-driving cars to medical imaging. A key component of many object detection algorithms is Non-Maximum Suppression (NMS), a technique used to filter out redundant bounding box predictions and select the most confident one for each detected object. Traditional NMS relies on predefined anchor boxes, which are pre-defined bounding box sizes and locations that act as templates for potential objects. While effective, these anchor boxes can be static and may not accurately represent the diverse shapes and scales of objects in real-world images. This can lead to...