Lightweight Aerial Object Detection Method Based on Improved RetinaNet
Aiming at the problems of smaller targets,different scales and large number of model parameters of target detection algorithm in UAV aerial images,a lightweight target detection algorithm model,Retinanet-S,based on RetinaNet is proposed.Firstly,GhostNetV2 is used as the lightweight back-bone to enhance the characteristic information of the targets.Secondly,while the lightweight modules GSConv and VoV-GSCSP are used in the neck to ensure the detection accuracy and to reduce the number of model parameters.Finally,the Loss function is improved into Focal SIoU Loss to further improve the accuracy of the model.Through the experiment on VisDrone2019 dataset,the parameter amount of RetinaNet-S is only 5.52 M,the detection speed is increased by 9.55 FPS.
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