To address the issues of high false detection rates and low detection accuracy in remote sens-ing target detection due to small object sizes and large quantitie,an improved YOLOv7 model is proposed by using SPD-RConv to replace Repconv in the original network.And a Concat_SE adaptive channel fusion full connection layer,based on Concat and SE attention mechanism is introduced to enhance the focus on high-val-ue information.Then,the candidate boxes for the target are recalculated using the K-means clustering algo-rithm.The improved algorithm and the original algorithm are tested on the enhanced RSOD data set.The re-sults show that the improved algorithm increased the mAP value by 17.1%,and the precision and recall rates by 19.7%and 15.5%,respectively,which demonstrates that the improved YOLOv7 effectively enhances the model's ability to detect remote sensing targets.
维普
万方数据