基于显著图数据增强的飞行器识别与检测算法

Data Augmentation Method Based on Saliency Map for Aircraft Identification and Detection Technology

数据增强技术能够有效解决民用航空等领域机器学习模型训练数据严重不足的问题,对于提升智能模型的性能至关重要。为此,针对航空领域飞行器识别和检测的典型应用场景,本文提出基于显著图的数据增强方法,在不同种类的飞行器数据集上分别进行分类和检测试验。试验结果表明,在飞行器目标检测数据集上,利用本文提出的数据增强方法可以提升飞行器目标检测精度。

With the development of artificial intelligence application in aviation domain,artificial intelligence technology also plays an important role in classification and detection tasks.This paper focuses on the data augmentation methods in the field of computer vision,which proposes a data augmentation algorithm based on improved saliency map and conducts classification and detection experiments on different kinds of aircraft data sets.Experiments show that the data augmentation algorithm based on the improved saliency map has better performance in the aircraft identification and detection tasks.