Anchor Boxes: Shaping Object Detection with Aspect Ratios
Beyond the Rectangle: How Anchor Box Aspect Ratios Shape Object Detection Object detection, the cornerstone of many computer vision applications, relies on identifying and localizing objects within images. While Convolutional Neural Networks (CNNs) excel at feature extraction, they need guidance to pinpoint these objects accurately. This is where anchor boxes come into play. Anchor boxes are predefined bounding boxes with specific dimensions placed across an image grid. These boxes serve as initial proposals for potential object locations, providing the CNN with a starting point for refining predictions. But did you know that the aspect ratio of these anchor boxes significantly impacts the performance of your object detection model? The Problem with Static Aspect Ratios: Traditional object detection models often utilize...