MAE-BG: dual-stream boundary optimization for remote sensing image semantic segmentation

MAE-BG: dual-stream boundary optimization for remote sensing image semantic segmentation

Deep learning has achieved remarkable performance in semantically segmenting remotely sensed images. However, the high-frequency detail loss caused by continuous convolution and pooling operations and the uncertainty introduced when annotating low-contrast objects with weak boundaries induce blurred...

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Bibliographic Details
Main Authors: Ruiqi Yang, Chen Zheng, Leiguang Wang, Yili Zhao, Zhitao Fu, Qinling Dai
Format: Article
Language:English
Published: Taylor & Francis Group 2023-12-01
Series:Geocarto International
Subjects:
deep learning
boundary optimization
squeeze and excitation
semantic segmentation
remote sensing
Online Access:http://dx.doi.org/10.1080/10106049.2023.2190622

Internet

http://dx.doi.org/10.1080/10106049.2023.2190622

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