Unsupervised domain adaptation with adversarial self-training for crop classification using remote sensing images

HIGHLIGHTS

• who: Geun-Ho Kwak and No-Wook Park from the Geoinformatic Engineering Research Institute, Inha University, Incheon, Korea have published the paper: Unsupervised Domain Adaptation with Adversarial Self-Training for Crop Classification Using Remote Sensing Images, in the Journal: (JOURNAL) of 25/04/2018
• what: To address the above-mentioned limitations, this study proposes a novel UDA framework called self-training with domain adversarial network (STDAN) tailored to crop classification using remote sensing images. In this study, the training data in the source domain and the unlabeled training data in the target domain were collected . . .
  

   

  

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