Comparison of deep transfer learning algorithms and transferability measures for wearable sleep staging

HIGHLIGHTS

• who: Samuel H. Waters from the Department of Bioengineering, Atlanta, United States, Emory University have published the research work: Comparison of deep transfer learning algorithms and transferability measures for wearable sleep staging, in the Journal: (JOURNAL)
• what: For this work, the authors also used a modified version of CORAL of the own design which takes class into account when learning the transformations. That is, DDC works by incentivizing the model to learn a similar hidden-layer representation across both source and target datasets, so if the layer it is applied to already generalizes well between . . .
  

   

  

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