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Title

White Blood Cell Types Classification Using Deep Learning Models

Author

Rufaidah Ali Bagido1 Manar Alzahrani2 Muhammad Arif

Citation

Vol. 21  No. 9  pp. 223-229

Abstract

Classification of different blood cell types is an essential task for human’s medical treatment. The white blood cells have different types of cells. Counting total White Blood Cells (WBC) and differential of the WBC types are required by the physicians to diagnose the disease correctly. This paper used transfer learning methods to the pre-trained deep learning models to classify different WBCs. The best pre-trained model was Inception ResNetV2 with Adam optimizer that produced classification accuracy of 98.4% for the dataset comprising four types of WBCs.

Keywords

Deep Learning, Blood Cells Classification, Transfer Learning

URL

http://paper.ijcsns.org/07_book/202109/20210930.pdf