Evaluating the proposed framework’s accuracy in binary and multiclassification scenarios against the baseline DL models.

مواد مشابهة

• Three types of models are compared using the Accuracy metric for multiclassification in an imbalanced CTG test dataset: basic deep learning models, advanced deep learning models, and the proposed framework.
  حسب: Amin Ullah (12015113)
  منشور في: (2025)
• Using the Recall, Precision, and F1-score metrics, three model types—naive deep learning models, advanced deep learning models, and the proposed framework—are compared for multiclassification of the Pathological minor class in an imbalanced CTG test dataset.
  حسب: Amin Ullah (12015113)
  منشور في: (2025)
• Using the Recall, Precision, and F1-score metrics, three model types are compared: naïve deep learning models, advanced deep learning models, and the proposed framework for multiclassification of Suspicious minor class in an imbalanced CTG test dataset.
  حسب: Amin Ullah (12015113)
  منشور في: (2025)
• Using the Accuracy metric, three model types—naive deep learning models, advanced deep learning models, and the proposed framework—are compared for the binary classification of normal and abnormal classes in an unbalanced CTG test dataset.
  حسب: Amin Ullah (12015113)
  منشور في: (2025)
• Using the Recall, Precision, and F1-score metrics, three model types are compared: naïve deep learning models, advanced deep learning models, and the proposed framework for binary classification of abnormal class in an imbalanced CTG test dataset.
  حسب: Amin Ullah (12015113)
  منشور في: (2025)