现代雷达2025，Vol.47Issue(11)：22-28,7.DOI:10.16592/j.cnki.1004-7859.2025062903
基于多模态特征融合与动态注意力机制的目标识别算法
An Object Recognition Algorithm Based on Multi-modal Feature Fusion and Dynamic Attention Mechanism
摘要
Abstract
Aiming at the problem that single-modal object recognition is easily affected by climate and interference,an object recogni-tion algorithm based on multi-modal image feature fusion is proposed.The proposed method is divided into the following four primary steps.In the first step,multi-modal images are preprocessed,during which the visible light,infrared,and SAR images of the ground scene are augmented respectively based on their modality-specific characteristics to enhance the model's generalization ability and ro-bustness.Next,corresponding classification labels are assigned to each image.Subsequently,different deep learning networks are designed to train data with different modalities separately,and the classification heads of all pre-trained networks are then removed.Finally,each classification network is connected to the feature fusion module for a retraining,so as to improve the classification accu-racy of the object classification.The method proposed in this paper accomplishes information complementation by employing multi-modal image feature fusion for object recognition,thereby achieving efficient identification of space objects.Experimental results demonstrate that the proposed algorithm achieves a high recognition accuracy of 96.74%on the WHU-OPT-SAR dataset.关键词
复杂电磁环境/多模态/特征融合/动态注意力机制/目标识别Key words
complex electromagnetic environment/multi-modality/feature fusion/dynamic attention mechanism/object recognition分类
信息技术与安全科学引用本文复制引用
丛潇雨,戴少怀,陈铖,单世臣,韩玉兵..基于多模态特征融合与动态注意力机制的目标识别算法[J].现代雷达,2025,47(11):22-28,7.基金项目
上海航天科技创新基金资助项目(SAST2023-001) （SAST2023-001）
江苏省卓越博士后计划资助项目(2023ZB124) （2023ZB124）
国家自然科学基金资助项目(62371236) （62371236）
