LKAFFNet: A Novel Large-Kernel Attention Feature Fusion Network for Land Cover Segmentation
The accurate segmentation of land cover in high-resolution remote sensing imagery is crucial for applications such as urban planning, environmental monitoring, and disaster management. However, traditional convolutional neural networks (CNNs) struggle to balance fine-grained local detail with large-...
Saved in:
Main Authors: | Bochao Chen, An Tong, Yapeng Wang, Jie Zhang, Xu Yang, Sio-Kei Im |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2024-12-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/25/1/54 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Attention-Guided Shared Hybrid Network for Enhanced Land Cover Segmentation
by: Yinbing Jiang, et al.
Published: (2025-01-01) -
Restoration of Degraded Agricultural Land
by: Alex, Saturday
Published: (2018) -
LAND COVER CHANGES IN ROMANIA BASED ON CORINE LAND COVER INVENTORY 1990–2012
by: JENICĂ HANGANU, et al.
Published: (2015-12-01) -
Land cover classification for Siberia leveraging diverse global land cover datasets
by: Munseon Beak, et al.
Published: (2025-01-01) -
Paradigm of Financial Provision of the Agricultural Land Restoration in Ukraine
by: Nadiya Davydenko, et al.
Published: (2017-12-01)