Deep Learning Network Intensification for Preventing Noisy-Labeled Samples for Remote Sensing Classification

Deep Learning Network Intensification for Preventing Noisy-Labeled Samples for Remote Sensing Classification

The deep-learning-network performance depends on the accuracy of the training samples. The training samples are commonly labeled by human visual investigation or inherited from historical land-cover or land-use maps, which usually contain label noise, depending on subjective knowledge and the time o...

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Bibliographic Details
Main Authors: Chuang Lin, Shanxin Guo, Jinsong Chen, Luyi Sun, Xiaorou Zheng, Yan Yang, Yingfei Xiong
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Remote Sensing
Subjects:
noisy labels
deep learning
building extraction
attention network
Online Access:https://www.mdpi.com/2072-4292/13/9/1689

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https://www.mdpi.com/2072-4292/13/9/1689

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