Journal Article
Under ReviewQ1XceptionKNN: A Hybrid Model for WBC Classification with Comparative Analysis of CLAHE, Macenko, and Vahadane Normalization Algorithms
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Journal / Venue
Journal of machine learning Research
Paper Link
Not AvailableJournal Metrics
Metrics Updated: April 2026MIT Press
Impact Factor
5.2
Quartile
Q1
Keywords
White Blood CellDeep LearningMachine LearningTransfer LearningXceptionKNNFeature SelectionMacenkoVahadaneCLAHE
Authors
Faysal Ahmmed
faysalahmmed4200@gmail.comAjmy Alaly
alalyajmy@gmail.comSamanta Mehnaj
samantamehnaj2001@gmail.comMohaimen-Bin-Noor
mohaimen.niloy@aiub.eduOverview
Developed XceptionKNN, a hybrid deep learning–machine learning model for accurate WBC classification across eight types, integrating advanced preprocessing (CLAHE, Macenko, Vahadane), feature selection, and KNN for robust clinical decision support.
Abstract
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