UAV detection based on rainy environment
Kai Luo, Rongjian Luo, Youwei Zhou · 2021
Based on the UAV detection is under the rainy day will remove the rain to UAV for the front-end process highlighted in depth study methods. Target detection technology has made great progress in recent years. But when it comes to low-flying drones, especially in the case of environmental impacts such as rain and fog. the accuracy and robustness can not meet the real-time requirement. Based on the existing results, this paper uses deep convolutional neural network to detect UAV. First,. introduce the current image fog removal, rain removal related algorithms, using the basic DID-MDN algorithm to achieve rain removal. Second, introduce the algorithm of target detection, and YOLOv5 based on deep learning is used for target detection.