SMFE-Net: a saliency multi-feature extraction framework for VHR remote sensing image classification

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成果类型：

期刊论文

作者：

Chen, Junsong;Yi, Jizheng;Chen, Aibin;Yang, Ke;Jin, Ze

通讯作者：

Yi, JZ

作者机构：

[Yi, Jizheng; Yang, Ke; Chen, Junsong; Chen, Aibin; Yi, JZ] Cent South Univ Forestry & Technol, Coll Comp & Informat Engn, Changsha 410000, Peoples R China.

[Yi, Jizheng; Yang, Ke; Chen, Junsong; Chen, Aibin; Yi, JZ] Cent South Univ Forestry & Technol, Inst Artificial Intelligence Applicat, Changsha 410000, Peoples R China.

[Yi, Jizheng; Chen, Aibin; Yi, JZ] Hunan Key Lab Intelligent Logist Technol, Changsha 410000, Peoples R China.

[Jin, Ze] Informat & Artificial Intelligence Res Int Hub Grp, Suzuki Lab, Tokyo 2268503, Japan.

[Jin, Ze] Tokyo Inst Technol, Inst Innovat Res, Lab Future Interdisciplinary Res Sci & Technol, Tokyo 2268503, Japan.

通讯机构：

[Yi, JZ ] C

Cent South Univ Forestry & Technol, Coll Comp & Informat Engn, Changsha 410000, Peoples R China.

Cent South Univ Forestry & Technol, Inst Artificial Intelligence Applicat, Changsha 410000, Peoples R China.

Hunan Key Lab Intelligent Logist Technol, Changsha 410000, Peoples R China.

语种：

英文

关键词：

Very-high resolution (VHR) remote sensing image;Saliency multi-feature extraction;Attention mechanism;Remote sensing scene classification

期刊：

Multimedia Tools and Applications

ISSN：

1380-7501

年：

2024

卷：

期：

页码：

3831-3854

DOI：

10.1007/s11042-023-15759-2

基金类别：

Hunan Provincial Natural Science Foundation of China [2022JJ31022]; Undergraduate Education Reform Project of Hunan Province [HNJG-2021-0532]; National Natural Science Foundation of China [61602528]

机构署名：

本校为第一且通讯机构

院系归属：

计算机与信息工程学院

摘要：

Scene classification of very-high resolution (VHR) remote sensing images is a challenging research hotspot. It is difficult to extract salient features because of the characteristics of remote sensing images, such as large spatial range changes and complex scenes. In addition, the effective combination of high-level semantic information and low-level contour information is also a major difficulty at present. In order to solve these problems, we proposed a new end-to-end saliency multi-feature extraction network (SMFE-Net) based on VGG16 and long short-term memory (LSTM) to extract salient feat...

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