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MSALNet:a multi-scale adaptive learning network for high-resolution remote sensing scene classification

Chao Yang Chengbo Wei Yiming Zhao Liming Wang Peigang Xu Kunlun Qi Yuanzheng Shao Huayi Wu

地球空间信息科学学报（英文版）2026，Vol.29Issue(1)：中插7,143-167,26.

地球空间信息科学学报（英文版）2026，Vol.29Issue(1)：中插7,143-167,26.DOI:10.1080/10095020.2025.2514822

MSALNet:a multi-scale adaptive learning network for high-resolution remote sensing scene classification

Chao Yang ¹Chengbo Wei ¹Yiming Zhao ¹Liming Wang ²Peigang Xu ³Kunlun Qi ¹Yuanzheng Shao ⁴Huayi Wu⁴

作者信息

1. National Engineering Research Center of Geographical Information System,China University of Geosciences,Wuhan,China
2. China Mobile(Hangzhou)Information Technology Co.,Ltd.,Hangzhou,China
3. First Institute of Photogrammetry and Remote Sensing,MNR,Xi'an,China
4. Collaborative Innovation Center of Geospatial Technology,Wuhan University,Wuhan,China
折叠

摘要

关键词

Remote sensing scene classification/convolutional neural network(CNN)/scale effect/multiscale feature fusion/scale adaptive

Key words

Remote sensing scene classification/convolutional neural network(CNN)/scale effect/multiscale feature fusion/scale adaptive

引用本文复制引用

Chao Yang,Chengbo Wei,Yiming Zhao,Liming Wang,Peigang Xu,Kunlun Qi,Yuanzheng Shao,Huayi Wu..MSALNet:a multi-scale adaptive learning network for high-resolution remote sensing scene classification[J].地球空间信息科学学报（英文版）,2026,29(1):中插7,143-167,26.

基金项目

This work was supported in part by the National Natural Science Foundation of China[grant number 42371428],in part by the National Key R&D Program of China[grant number 2024YFB3908605],Special Fund of Hubei Luojia Laboratory[grant number 220100034],in part by the Open Fund of Hubei Luojia Laboratory[grant number 220100056]. （）

地球空间信息科学学报（英文版）

ISSN：1009-5020

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