High-Resolution Remote Sensing Imagery Classification of Imbalanced Data Using Multistage Sampling Method and Deep Neural Networks

High-Resolution Remote Sensing Imagery Classification of Imbalanced Data Using Multistage Sampling Method and Deep Neural Networks

Class imbalance is a key issue for the application of deep learning for remote sensing image classification because a model generated by imbalanced samples training has low classification accuracy for minority classes. In this study, an accurate classification approach using the multistage sampling...

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Bibliographic Details
Main Authors: Wei Xia, Caihong Ma, Jianbo Liu, Shibin Liu, Fu Chen, Zhi Yang, Jianbo Duan
Format: Article
Language:English
Published: MDPI AG 2019-10-01
Series:Remote Sensing
Subjects:
high-resolution remote sensing image
classification
deep learning
imbalanced data
multistage sampling
aspp
encoder-decoder
Online Access:https://www.mdpi.com/2072-4292/11/21/2523

Internet

https://www.mdpi.com/2072-4292/11/21/2523

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