Anchor Boxes: Balancing Accuracy with Efficiency
The Anchor Dilemma: Balancing Accuracy with Efficiency in Object Detection Object detection, the ability of a computer to identify and locate objects within an image, is a cornerstone of modern AI. This powerful technology fuels applications ranging from self-driving cars to facial recognition, revolutionizing how we interact with the digital world. One crucial component of object detection algorithms is the concept of anchor boxes. These are pre-defined bounding boxes of various sizes and aspect ratios that act as templates for potential objects in an image. The algorithm predicts offsets and confidence scores for each anchor box, ultimately determining whether an object exists and where it's located. But here's the catch: the number of anchor boxes directly influences both the accuracy...