Autor:

Awais, Muhammad ; Akram, Tallha ; Alasiry, Areej ; Marzougui, Mehrez ; Park, Jongwoon ; Chang, Byoungchol

Współtwórca:

Woźniak, Marcin - ed. ; Kumar, Yogesh - ed. ; Ijaz, Muhammad Fazal - ed.

Tytuł:

An expert system for leukocyte classification using probabilistic deep feature optimization via distribution estimation

Podtytuł:

.

Tytuł publikacji grupowej:

AMCS, volume 34 (2024)

Temat i słowa kluczowe:

convolutional neural networks ; optimization ; evolutionary algorithms ; classification ; machine learning

Abstract:

White blood cells (WBCs) are essential for immune and inflammatory responses, and their precise classification is crucial for diagnosing and managing diseases. Although convolutional neural networks (CNNs) are effective for image classification, their high computational demands necessitate feature selection to enhance efficiency and interpretability. This study utilizes transfer learning with EfficientNet-B0 and DenseNet201 to extract features, along with a Bayesian-based feature selection method with a novel optimization mechanism to improve convergence. The reduced feature set is classified using soft voting across multiple classifiers. Tests on benchmark datasets achieved over 99% accuracy with fewer features, surpassing or matching existing methods.

Wydawca:

Zielona Góra: Uniwersytet Zielonogórski

Data wydania:

2024

Typ zasobu:

artykuł

DOI:

10.61822/amcs-2024-0039

Strony:

579-595

Źródło:

AMCS, volume 34, number 4 (2024) ; kliknij tutaj, żeby przejść

Jezyk:

eng

Licencja CC BY 4.0:

kliknij tutaj, żeby przejść

Prawa do dysponowania publikacją:

Biblioteka Uniwersytetu Zielonogórskiego