Using Modified YOLOv4 for Military Target Detection

Abstract

We propose methods for object detection based on remote sensing images. This method further improves detection accuracy and decreases error rates. Modified YOLOv4 is an accelerated neural network model based on the YOLO (YouOnly-Look-Once) object detection method. It outperforms existing networks in terms of execution time and detection performance. The experimental results show improved mAP (mean average precision) performance of the proposed method for object detection in remote sensing images. We thus propose a novel system for automatic object detection for high-resolution remote sensing images.