Anchor-based methods

Anchor-based methods are techniques used in object detection where predefined reference points or "anchors" are placed across an image at various scales and aspect ratios. These anchors act as starting points for the model to evaluate whether an object exists nearby and to refine its size and location. Essentially, they help the model efficiently identify objects by matching these fixed templates to different parts of an image, simplifying the process of detecting objects like cars, people, or animals across diverse positions and sizes.