Semi-supervised contrastive learning for few-shot segmentation of remote sensing images

HIGHLIGHTS

• who: Yadang Chen and collaborators from the Engineering Research Center Digital Forensics, Ministry Education, Nanjing University Information Science and Technology, Nanjing, China have published the article: Semi-Supervised Contrastive Learning for Few-Shot Segmentation of Remote Sensing Images, in the Journal: (JOURNAL)
• what: Experiments on the Vaihingen dataset and the Zurich Summer dataset show that the model has satisfactory in-domain and cross-domain transferring abilities. The authors propose a few-shot segmentation of the remote sensing images model using a self-supervised background learner to overcome the problem of feature undermining and discriminator bias . . .
  

   

  

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