AnchorNone

AnchorNone refers to a technique in machine learning, particularly in object detection, where predefined anchor boxes—shapes used to identify objects in images—are not utilized. Instead, the model learns to determine object shapes and sizes directly from the data without relying on these anchor boxes as starting points. This approach can enhance flexibility and accuracy, allowing the system to adapt better to various object forms and sizes within images. By avoiding predefined anchors, models can potentially improve performance in detecting and classifying objects in diverse scenarios.