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

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Bibliografske podrobnosti
izdano v:	Applied Computational Intelligence and Soft Computing vol. 2025 (2025)
Glavni avtor:	Tani, Ishrat Zahan
Drugi avtorji:	Kah Ong Michael Goh, Islam, Md Nazmul, Md Tarek Aziz, Mahmud, S M Hasan, Nandi, Dip
Izdano:	John Wiley & Sons, Inc.
Teme:	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
Online dostop:	Citation/Abstract Full Text Full Text - PDF
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