The combination of backbone feature layers happens in the neck. It is also useful to split object detectors into two categories: one-stage detectors and two stage detectors. Detection happens in the head. Two-stage detectors decouple the task of object localization and classification for each ...
The YOLO (You Only Look Once) v7 model is the latest in the family of YOLO models. YOLO models are single stage object detectors. In a YOLO model, image frames are featurized through a backbone. These features are combined and mixed in the neck, and then they are passed along to the ...
In this article we will discuss about YOLOv11, a highly efficient object detection model that offers faster speeds, improved accuracy, and seamless integrati…
Detectron2 is built on a modular design that enables users to easily plug in various backbones networks, heads, and losses. The framework's backbone networks are typically convolutional neural networks that extract features from an image. These features are then fed into heads, which are responsib...