Classifying white blood cells using combining different convolutional neural networks

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dc.contributor.authorToptaş, Murat
dc.contributor.authorToptaş, Buket
dc.contributor.authorHanbay, Davut
dc.date.accessioned2026-04-04T13:18:54Z
dc.date.available2026-04-04T13:18:54Z
dc.date.issued2025
dc.departmentİnönü Üniversitesi
dc.description.abstractWhite blood cells are warrior cells that protect the human body against external factors. Each of these warrior cells performs a distinct task, making every piece of information about them highly valuable in the medical field. In this article, a classification framework for the four known types of white blood cells is proposed. It is hoped that the classification of these types will contribute to the prediction of diseases such as AIDS, malaria, leukemia, and many others. In the proposed method, images of white blood cells from the Blood Cell Classification and Detection dataset were used as input to Convolutional Neural Networks. The feature vectors extracted using these Convolutional Neural Network architectures were combined into a single vector. A Minimum Redundancy Maximum Relevance algorithm was then employed to identify the most effective features within the feature vector. Experiments were conducted using these selected features, and the analysis of each experiment was reported in detail. The Support Vector Machines classifier achieved an accuracy of 98.63% in classifying white blood cell types by combining features from multiple deep learning architectures. The experimental results demonstrated that the features obtained from different layers of the Convolutional Neural Networks had varying impacts on the classification performance. © The Author(s) 2025.
dc.description.sponsorshipTürkiye Bilimsel ve Teknolojik Araştırma Kurumu, TUBITAK
dc.identifier.doi10.1007/s11042-025-20879-y
dc.identifier.endpage44112
dc.identifier.issn1380-7501
dc.identifier.issue35
dc.identifier.scopus2-s2.0-105004465940
dc.identifier.scopusqualityQ1
dc.identifier.startpage44089
dc.identifier.urihttps://doi.org/10.1007/s11042-025-20879-y
dc.identifier.urihttps://hdl.handle.net/11616/107987
dc.identifier.volume84
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherSpringer
dc.relation.ispartofMultimedia Tools and Applications
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_Scopus_20250329
dc.subjectCell classification
dc.subjectConvolution neural networks
dc.subjectTypes of white blood cells
dc.subjectWhite blood cells
dc.titleClassifying white blood cells using combining different convolutional neural networks
dc.typeArticle

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