SSD (Single Shot Multi Box Detector) is one of the commonly used object detection algorithms known for its fast detection speed and high accuracy. However, SSD's performance in detecting objects of different scales is suboptimal. This paper proposes the RSF-SSD network based on multi-level feature enhancement. By improving the backbone network of SSD, skip-connections and channel attention mechanism are introduced into VGG16. This operation enhances the ability of the backbone network to extract detailed features. In the feature fusion module, an improved FPN (Feature Pyramid Networks) + PAN (...
