• Corpus ID: 239616447

Rethinking Generalization Performance of Surgical Phase Recognition with Expert-Generated Annotations

  title={Rethinking Generalization Performance of Surgical Phase Recognition with Expert-Generated Annotations},
  author={Seungbum Hong and Jiwon Lee and Bokyung Park and Ahmed A. Alwusaibie and Anwar H. Alfadhel and Sunghyun Park and Woo Jin Hyung and Min-Kook Choi},
As the area of application of deep neural networks expands to areas requiring expertise, e.g., in medicine and law, more exquisite annotation processes for expert knowledge training are required. In particular, it is difficult to guarantee generalization performance in the clinical field in the case of expert knowledge training where opinions may differ even among experts on annotations. To raise the issue of the annotation generation process for expertise training of CNNs, we verified the… 



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