计算机技术与发展2025，Vol.35Issue(10)：71-80,10.DOI:10.20165/j.cnki.ISSN1673-629X.2025.0118
自适应加权组合卷积的遥感舰船目标检测方法
Remote Sensing Ship Target Detection in Remote Sensing via Adaptive Weighted Combinatorial Convolution
摘要
Abstract
Remote sensing ship target detection and classification aims to accurately identify and locate ship targets in remote sensing images,thereby providing effective technical support for military reconnaissance,maritime rescue,ocean monitoring,and maritime traffic management.To address the challenge of fine-grained ship classification amid complex backgrounds and similar categories,we propose an adaptive weighted combination convolutional ship target detection method based on a two-stage fine-grained detection model.On the one hand,by integrating the efficiency of standard convolution in extracting basic target features with the advantages of dilated convolution in enlarging the receptive field and capturing multi-scale contextual information,the proposed method achieves an effective fusion of local and global features,which enhances the emphasis on ship targets while reducing background interference.On the other hand,the model adaptively adjusts feature extraction at multiple scales by computing variance,spatial,and edge information,and dynamically reassigns the convolutional operations through optimizing threshold calculation weights with the aid of both global and historical data,thereby improving its adaptability in complex scenarios.Experimental results show that the proposed method achieves average accuracies of 55.83%and 59.06%on the ShipRSImageNet and MAR20 datasets,surpassing the baseline by 3.56 percentage pointsand1.68 percentage points,respectively,demonstrating its effectiveness and robustness in fine-grained ship recognition under complex scenarios.关键词
细粒度/遥感舰船图像/目标检测/多尺度融合/深度学习Key words
fine-grained/remotely sensed ship images/object detection/multi-scale fusion/deep learning分类
信息技术与安全科学引用本文复制引用
陈云菲,王飞,况立群,韩燮,郭耀武..自适应加权组合卷积的遥感舰船目标检测方法[J].计算机技术与发展,2025,35(10):71-80,10.基金项目
国家自然科学基金(62272426) （62272426）
山西省科技重大专项计划"揭榜挂帅"项目(202201150401021) （202201150401021）
