宿州学院学报2024，Vol.39Issue(6)：13-17,32,6.DOI:10.3969/j.issn.1673-2006.2024.06.003
融合注意力引导的遥感影像场景分类方法研究
Research on Scene Classification Method of Remote Sensing Images with Integrated Attention Guidance
摘要
Abstract
In order to address the challenge of disentangling the main subject from the background information in re-mote sensing imagery,which often complicates the extraction of effective features for scene classification tasks,a no-vel method for remote sensing image scene classification that incorporates fused attention guidance is proposed.This method seamlessly integrates a fused attention module with ShuffleNet unit modules into the lightweight network ShuffleNetV2.This integration empowers the network to effectively capture both spatial structural details and channel weighting information from remote sensing imagery,thereby synthesizing meaningful semantic insights from the ima-ges and concentrating on the core and pivotal elements of the images;this approach significantly enhances the net-work's ability to recognize features while maintaining a lightweight model.Experimental comparisons,conducted on three widely utilized public remote sensing datasets—UCM,AID and NWPU—demonstrate that the proposed method surpasses other approaches in terms of performance,thus substantiating its effectiveness.关键词
遥感影像/场景分类/注意力机制/轻量级网络/特征提取Key words
Remote sensing image/Scene classification/Attention mechanism/Lightweight network/Feature extrac-tion分类
信息技术与安全科学引用本文复制引用
秦望博,葛斌,彭曦晨..融合注意力引导的遥感影像场景分类方法研究[J].宿州学院学报,2024,39(6):13-17,32,6.基金项目
国家自然科学基金(62102003) （62102003）
国家重点研发计划(2020YFB1314103) （2020YFB1314103）
安徽省自然科学基金(2108085QF258) （2108085QF258）
安徽省博士后基金(2022B623). （2022B623）
