Addressing Label Noise in Colorectal Cancer Classification Using Cross-Entropy Loss and pLOF Methods With Stacking-Ensemble Technique

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Opis bibliograficzny
Wydane w:	Applied Computational Intelligence and Soft Computing vol. 2025 (2025)
1. autor:	Tani, Ishrat Zahan
Kolejni autorzy:	Kah Ong Michael Goh, Islam, Md Nazmul, Md Tarek Aziz, Mahmud, S M Hasan, Nandi, Dip
Wydane:	John Wiley & Sons, Inc.
Hasła przedmiotowe:	Europe Feature extraction Outliers (statistics) Accuracy Labels Datasets Classification Applications programs Noise prediction Public health Medical imaging Feature selection Diagnosis Colorectal cancer Machine learning Entropy Data augmentation Medical prognosis Feces Image filters Cancer Neural networks Medical research Support vector machines Computer aided design > CAD Literature reviews Deep learning Trustworthiness Metamodels
Dostęp online:	Citation/Abstract Full Text Full Text - PDF
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