Enhancing the ophthalmic ai assessment with a fundus image quality classifier using local and global attention mechanisms

HIGHLIGHTS

• What: The authors propose the use of a salience map as a post hoc interpretability tool.
• Who: Shengzhan Wang from the Yat-sen University, China have published the paper: Enhancing the ophthalmic AI assessment with a fundus image quality classifier using local and global attention mechanisms, in the Journal: (JOURNAL)
• How: To validate the performance of the approach the authors used an external dataset and noise dataset. The multi-source heterogeneous fundus (MSHF) dataset is collected and then serves as an input to train the local and global attention aggregated deep neural_network (LGAANet . . .
  

   

  

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