Research on Aircraft Target Detection in Remote Sensing Images Based on Improved YOLOv8
To address the issues of low detection accuracy and missed detections in aircraft target detection in remote sensing images,an improved algorithm for aircraft target detection in remote sensing images based on the YOLOv8 algorithm is proposed.Firstly,embed the coordinate attention mechanism module into the convolutional module to extract small aircraft targets in complex backgrounds.Then,the detection head was optimized by removing large object detection heads,which improved the detection ability of small objects while reducing the computational complexity of the algorithm.Finally,using WIoU as an improved loss function to improve detection accuracy.The experiment shows that the improved YOLOv8 algorithm can effectively improve the accuracy of aircraft detection and is suitable for aircraft target detection in remote sensing images.
万方数据
维普
