Hyperspectral image classification with imbalanced data based on semi-supervised learning

HIGHLIGHTS

• who: Firstname Lastname and colleagues from the Center for Geo-Spatial Information, Shenzhen Institute of Advanced Technology, Chinese Academy of University of Chinese Academy of Sciences, Beijing, China have published the paper: Hyperspectral Image Classification with Imbalanced Data Based on Semi-Supervised Learning, in the Journal: (JOURNAL) of 25/08/2017
• what: The authors propose a novel semi-supervised learning-based preprocessing solution called NearPseudo. The authors propose a novel preprocessing solution called NearPseudo, to utilize the natural features of unlabeled data to improve the classification of imbalanced data; NearPseudo generates pseudo-labels for unlabeled . . .
  

   

  

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