White Blood Cell Types Classification Using Deep Learning Models
White Blood Cell Types Classification Using Deep Learning Models

국제컴퓨터통신보호논문지학회
International Journal of Computer Science & Network Security
Vol.21 No.9
2021.01

223 - 229 (7 pages)

커버이미지 없음

외부링크

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.

White Blood Cell Types Classification Using Deep Learning Models
White Blood Cell Types Classification Using Deep Learning Models

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White Blood Cell Types Classification Using Deep Learning Models White Blood Cell Types Classification Using Deep Learning Models

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White Blood Cell Types Classification Using Deep Learning Models
White Blood Cell Types Classification Using Deep Learning Models