信息工程大学学报2026，Vol.27Issue(1)：56-63,8.DOI:10.3969/j.issn.1671-0673.2026.01.008
基于迁移学习与运动特征融合的机型分类识别方法
A Method for Aircraft Model Classification Based on Transfer Learning Combined with Motion Features
摘要
Abstract
To address the issue of low aircraft classification accuracy caused by the scarcity of high-precision labeled data,which hinders effective model training,an aircraft classification and recognition method based on transfer learning and motion feature fusion is proposed.Firstly,differences in motion characteristics of different types of aircraft are analyzed.Subsequently,the RGB algorithm is employed to transform motion-differentiated features into trajectory images that encapsulate both trajectory shape information and target motion attributes.Finally,for scenarios with limited sample data,a transfer learning strategy is introduced,fine-tuning and optimizing a pre-trained ResNet model to accomplish aircraft model classification and recognition.Experimental results demonstrate that the proposed method achieves an aircraft model classification accuracy of 75.6%on small-sample datasets,outper-forming baseline models by an improvement of 11 to 15.3 percentage points.关键词
机型分类识别/广播式自动相关监视系统/RGB算法/联合运动特征/迁移学习Key words
aircraft model classification/automatic dependent surveillance broadcast system/RGB al-gorithm/joint motion features/transfer learning分类
信息技术与安全科学引用本文复制引用
葛成龙,张静,杜剑平,吴优..基于迁移学习与运动特征融合的机型分类识别方法[J].信息工程大学学报,2026,27(1):56-63,8.
