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

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

High-resolution remote sensing (HRS) images often feature objects of varying sizes within the same scene, presenting significant challenges for conventional CNN with fixed-size receptive fields. To address this issue, we propose a multi-scale adaptive learning network (MSALNet) that learns optimal s...

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Bibliographic Details
Main Authors: Chao Yang, Chengbo Wei, Yiming Zhao, Liming Wang, Peigang Xu, Kunlun Qi, Yuanzheng Shao, Huayi Wu
Format: Article
Language:English
Published: Taylor & Francis Group 2025-06-01
Series:Geo-spatial Information Science
Subjects:
Remote sensing scene classification
convolutional neural network (CNN)
scale effect
multiscale feature fusion
scale adaptive
Online Access:https://www.tandfonline.com/doi/10.1080/10095020.2025.2514822
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https://www.tandfonline.com/doi/10.1080/10095020.2025.2514822

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