GEA-MSNet: A Novel Model for Segmenting Remote Sensing Images of Lakes Based on the Global Efficient Attention Module and Multi-Scale Feature Extraction

GEA-MSNet: A Novel Model for Segmenting Remote Sensing Images of Lakes Based on the Global Efficient Attention Module and Multi-Scale Feature Extraction

The decrease in lake area has garnered significant attention within the global ecological community, prompting extensive research in remote sensing and computer vision to accurately segment lake areas from satellite images. However, existing image segmentation models suffer from poor generalization...

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Bibliographic Details
Main Authors: Qiyan Li, Zhi Weng, Zhiqiang Zheng, Lixin Wang
Format: Article
Language:English
Published: MDPI AG 2024-03-01
Series:Applied Sciences
Subjects:
remote sensing image
lake segmentation
neural network
attention mechanism
feature fusion
Online Access:https://www.mdpi.com/2076-3417/14/5/2144

Internet

https://www.mdpi.com/2076-3417/14/5/2144

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