Hyperspectral Image Classification with Imbalanced Data Based on Semi-Supervised Learning

Hyperspectral remote sensing image classification has been widely employed for numerous applications, such as environmental monitoring, agriculture, and mineralogy. During such classification, the number of training samples in each class often varies significantly. This imbalance in the dataset is o...

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Bibliografiset tiedot
Päätekijät: Xiaorou Zheng, Jianxin Jia, Jinsong Chen, Shanxin Guo, Luyi Sun, Chan Zhou, Yawei Wang
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: MDPI AG 2022-04-01
Sarja:Applied Sciences
Aiheet:
hyperspectral image
classification
imbalanced data
semi-supervised learning
nearest neighbors
pseudo-label
Linkit:https://www.mdpi.com/2076-3417/12/8/3943
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