Design and Implementation of Small Object Detection Experiment in UAV Image
In order to solve the problems such as target density,and occlusion in detecting the small objects of unmanned aerial vehicle(UAV)images,the convolutional attention,deep feature fusion,and multi-scale feature fusion modules are designed to enhance the local and semantic information,which can improve the capability of feature extraction in the small objects of UAV images.Meanwhile,the loss function is improved to accelerate the convergence of proposed model.The experimental results based on the VisDrone2019 dataset show that the proposed model improves the detection accuracy of small objects,reduces the probability of false and missed detections,and provides an experimental basis for small target detection in more complex scenes.
NETL
NSTL
万方数据
