Local–Global Multiscale Fusion Network for Semantic Segmentation of Buildings in SAR Imagery

Local–Global Multiscale Fusion Network for Semantic Segmentation of Buildings in SAR Imagery

The extraction of buildings from synthetic aperture radar (SAR) images poses a challenging task in the realm of remote sensing (RS). In recent years, convolutional neural networks (CNNs) have rapidly advanced and found application in the field of RS. Researchers have investigated the potential of CN...

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Bibliographic Details
Main Authors: Xuanyu Zhou, Lifan Zhou, Haizhen Zhang, Wei Ji, Bei Zhou
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Convolutional neural networks (CNNs)
dual encoder–decoder
semantic segmentation of buildings
synthetic aperture radar (SAR) images
transformer
Online Access:https://ieeexplore.ieee.org/document/10475426/

Internet

https://ieeexplore.ieee.org/document/10475426/

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