Human-Annotated Label Noise and Their Impact on ConvNets for Remote Sensing Image Scene Classification

Human-Annotated Label Noise and Their Impact on ConvNets for Remote Sensing Image Scene Classification

Human-labeled training datasets are essential for convolutional neural networks (ConvNets) in satellite image scene classification. Annotation errors are unavoidable due to the complexity of satellite images. However, the distribution of real-world human-annotated label noises on satellite images an...

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Bibliographic Details
Main Authors: Longkang Peng, Tao Wei, Xuehong Chen, Xiaobei Chen, Rui Sun, Luoma Wan, Jin Chen, Xiaolin Zhu
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Convolutional neural network (ConvNet)
human-annotated label noise
label noise
remote sensing
scene classification
Online Access:https://ieeexplore.ieee.org/document/10757363/
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