对基于深度学习的无人机航拍车辆检测研究

Research on UAV Aerial Photography Vehicle Detection Based on Deep Learning

开发无人机航拍车辆检测技术,从不同背景图像数据集中提取车辆特征,应采用科学算法提高检测准确率。基于此,对深度学习算法展开了分析,结合航拍车辆检测问题和影响检测精度的因素提出了检测方案。通过建立目标检测框架实现数据多尺度特征融合,做好网格、数据处理和模型训练,最终可以有效提高车辆检测精度,满足技术应用需求。

To develop UAV aerial photography vehicle detection technology to extract vehicle features from different background image data sets,scientific algorithms should be used to improve the detection accuracy.Based on this,the deep learning algorithm is analyzed,and a detection scheme is proposed in combination with the problem of aerial vehicle detection and the factors that affect the detection accuracy.By establishing a target detection framework,realizing multi-scale feature fusion of data,and doing a good job in grid,data processing and model training,the vehicle detection accuracy can be effectively improved and the technical application requirements can be met.