Research on Quality Evaluation Algorithm of Flight Training for National Day Parade Air Echelon

机译：国庆阅兵区航班训练质量评价算法研究

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In order to meet the requirements of real-time and accuracy for the quality evaluation of air echelon flight training during the National Day parade, a relevant algorithm for the quality evaluation of flight training by using fixed-point photography of ordinary cameras is proposed. The image rectification algorithm based on vanishing point theory is studied, which effectively solves the problem of image distortion and improves the accuracy of evaluation. This paper studies the air echelon automatic evaluation algorithm based on depth learning, realizes the automatic identification and evaluation of the air echelon in the image, and improves the evaluation speed.

机译：为了满足国庆日期游行期间空中梯队飞行训练质量评估的实时和准确性的要求，提出了一种利用普通摄像机定点摄影来训练质量评估的相关算法。研究了基于消失点理论的图像整流算法，有效解决了图像失真的问题，提高了评估的准确性。本文研究了基于深度学习的空气梯级自动评估算法，实现了图像中空气梯级的自动识别和评估，提高了评估速度。

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《International Conference on Computer Vision, Image and Deep Learning》|2020年|130-134|共5页
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Yao Chong; Lou Lizhu; Sui Xiaokui; Xu Ming;
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Aircraft; Cameras; Training; Atmospheric modeling; Optical distortion; Mathematical model; Real-time systems;

机译：飞机;相机;培训;大气的造型;光畸变;数学模型;实时系统;
入库时间 2022-08-26 13:54:44

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Research on Quality Evaluation Algorithm of Flight Training for National Day Parade Air Echelon

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