MFFSODNet: Multiscale Feature Fusion Small Object Detection Network for UAV Aerial Images

Unmanned aerial vehicle (UAV) aerial image object detection is a valuable and challenging research field. Despite the breakthrough of deep learning-based object detection networks in natural scenes, UAV images often exhibit characteristics such as a high proportion of small objects, dense distribution, and significant variations in object scales, posing great challenges for accurate detection. To address these issues, we propose an innovative multi-scale feature fusion small object detection network (MFFSODNet). First, concerning the high proportion of small objects in UAV images, an additional tiny object prediction head is introduced instead of the large object prediction head. This approach provides a good…

• NS
  Natural Science Foundation of Shaanxi Province

  Awards: 2019JQ-936, 2021GY-341, 2021JM-537