Remote sensing images target detection based on deep learning

Abstract

Target detection based on deep learning methods has important applications in the field of remote sensing images target detection. Aiming at the disadvantages of the small target scale for remote sensing images, this paper proposes an improved YOLOv4 algorithm to improve the detection effect of remote sensing images. The experimental results show that the algorithm proposed in this paper has an average accuracy rate of 2.25% higher than that of the original YOLOv4 algorithm. The accuracy of detecting small-scale targets has been significantly improved, and the amount of model parameters has also been reduced compared to the original algorithm.