Transformer based on channel-spatial attention for accurate classification of scenes in remote sensing image

HIGHLIGHTS

• who: Jingxia Guo from the Wuhan University have published the Article: Transformer based on channel-spatial attention for accurate classification of scenes in remote sensing image, in the Journal: Scientific Reports Scientific Reports
• what: The authors propose a CSAT learning scheme that combines the contributions mentioned above. The aim of this design strategy was to verify that the CSAM module can focus on the local features of the ordered patches before entering the transformer encoder, thereby improving the performance of the model, as described later. The authors used the overall accuracy as the evaluation criterion . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or E-mail:

  If you don't have an account, you can create one here.