A Label Correction Learning Framework for Gully Erosion Extraction Using High-Resolution Remote Sensing Images and Noisy Labels

A Label Correction Learning Framework for Gully Erosion Extraction Using High-Resolution Remote Sensing Images and Noisy Labels

Rapid and reliable gully erosion (GE) extraction from high-resolution remote sensing (HRRS) images is crucial for the development of land protection measures. For this task, semantic segmentation methods are widely considered the state-of-the-art solutions. Nevertheless, providing sufficient and cle...

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Bibliographic Details
Main Authors: Chunhui Zhao, Yi Shen, Nan Su, Yiming Yan, Shou Feng, Wei Xiang, Yong Liu, Tianhao Zhao
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Gully erosion (GE) extraction
high-resolution remote sensing images
land resource protection
noisy labels
semantic segmentation
Online Access:https://ieeexplore.ieee.org/document/10339800/

Internet

https://ieeexplore.ieee.org/document/10339800/

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