ESA ve Kon-DVM Modelleri Kullanarak Beyaz Kan Hücrelerinin Sınıflandırılması

Ekiz A., KAPLAN K., ERTUNÇ H. M.

29.IEEE Sinyal İşleme ve İletişim Uygulamaları Kurultayı, İstanbul, Türkiye, 09 Haziran 2021, ss.1-4 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/siu53274.2021.9477962
  • Basıldığı Şehir: İstanbul
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.1-4
  • Anahtar Kelimeler: white blood cells, classification, convolutional neural networks, support vector machines
  • Kocaeli Üniversitesi Adresli: Evet

Özet

White blood cells are one of the most important cells for the human body that make up the human immune system. These cells in the blood can contain important information for the diagnosis of many diseases as well as protecting the body. Nowadays, blood analysis performed by doctors can cause both waste of time and human errors. A support diagnosis system can be created to prevent these errors, to perform rapid diagnosis and to reduce the workload. In this study, 12442 white blood cell images consisting of four types of white blood cells were tried to be classified. These images were first classified with CNN (Convolutional Neural Networks), then classification is performed using Con-SVM (Convolutional features - Support Vector Machines). While an accuracy rate of 83.91% was obtained with the CNN model, an accuracy rate of 85.96% was observed with the Con-SVM model.