@article{ART003169009},
author={Junhwi Park and Changjoon Park and Namjung Kim and Ryumduck Oh and Jeonghwan Gwak},
title={Enhanced White Blood Cell Classification via YOLO-based Region-of-Interest Extraction and Feature Ensemble},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2025},
volume={30},
number={1},
pages={1-14}
TY - JOUR
AU - Junhwi Park
AU - Changjoon Park
AU - Namjung Kim
AU - Ryumduck Oh
AU - Jeonghwan Gwak
TI - Enhanced White Blood Cell Classification via YOLO-based Region-of-Interest Extraction and Feature Ensemble
JO - Journal of The Korea Society of Computer and Information
PY - 2025
VL - 30
IS - 1
PB - The Korean Society Of Computer And Information
SP - 1
EP - 14
SN - 1598-849X
AB - Blood is composed of white blood cells (WBC), red blood cells (RBC), and platelets, components closely related to human health. They respectively contribute to the immune system, the transfer of oxygen to body organs, and bleeding prevention. In the case of WBC, when abnormalities occur in the body, such as infections and allergic reactions, the relevant type of WBC in the blood increases to respond. Therefore, it is possible to identify the type of WBC in the case of abnormalities in the body through the application of deep learning-based object detection algorithms and classification methods.
This information can be used to predict the health status of patients easily. Therefore, this paper proposes a method for extracting the region of interest (RoI) for WBC and classifying WBC types based on blood microscope images using you-only-look-once (YOLO) and feature ensemble techniques.
We select RoI extraction models through a comparative analysis of WBC detection performance for YOLO V5, V8, V9 and YOLO-Neural Architecture Search (YOLO-NAS), and demonstrate an improvement in WBC type classification performance through comparative analysis and a Top-3 model feature ensemble based on general convolutional neural network (CNN) models, such as ResNet and EfficientNet. Compared to the approximately 98% performance of the Top-3 models based on the F1-Score, it achieved an improved performance of approximately 99%.
KW - Heterogeneous Feature Ensemble;Homogeneous Feature Ensemble;Image Classification;Object Detection;You-Only-Look-Once (YOLO);White Blood Cell
DO -
UR -
ER -
Junhwi Park, Changjoon Park, Namjung Kim, Ryumduck Oh and Jeonghwan Gwak. (2025). Enhanced White Blood Cell Classification via YOLO-based Region-of-Interest Extraction and Feature Ensemble. Journal of The Korea Society of Computer and Information, 30(1), 1-14.
Junhwi Park, Changjoon Park, Namjung Kim, Ryumduck Oh and Jeonghwan Gwak. 2025, "Enhanced White Blood Cell Classification via YOLO-based Region-of-Interest Extraction and Feature Ensemble", Journal of The Korea Society of Computer and Information, vol.30, no.1 pp.1-14.
Junhwi Park, Changjoon Park, Namjung Kim, Ryumduck Oh, Jeonghwan Gwak "Enhanced White Blood Cell Classification via YOLO-based Region-of-Interest Extraction and Feature Ensemble" Journal of The Korea Society of Computer and Information 30.1 pp.1-14 (2025) : 1.
Junhwi Park, Changjoon Park, Namjung Kim, Ryumduck Oh, Jeonghwan Gwak. Enhanced White Blood Cell Classification via YOLO-based Region-of-Interest Extraction and Feature Ensemble. 2025; 30(1), 1-14.
Junhwi Park, Changjoon Park, Namjung Kim, Ryumduck Oh and Jeonghwan Gwak. "Enhanced White Blood Cell Classification via YOLO-based Region-of-Interest Extraction and Feature Ensemble" Journal of The Korea Society of Computer and Information 30, no.1 (2025) : 1-14.
Junhwi Park; Changjoon Park; Namjung Kim; Ryumduck Oh; Jeonghwan Gwak. Enhanced White Blood Cell Classification via YOLO-based Region-of-Interest Extraction and Feature Ensemble. Journal of The Korea Society of Computer and Information, 30(1), 1-14.
Junhwi Park; Changjoon Park; Namjung Kim; Ryumduck Oh; Jeonghwan Gwak. Enhanced White Blood Cell Classification via YOLO-based Region-of-Interest Extraction and Feature Ensemble. Journal of The Korea Society of Computer and Information. 2025; 30(1) 1-14.
Junhwi Park, Changjoon Park, Namjung Kim, Ryumduck Oh, Jeonghwan Gwak. Enhanced White Blood Cell Classification via YOLO-based Region-of-Interest Extraction and Feature Ensemble. 2025; 30(1), 1-14.
Junhwi Park, Changjoon Park, Namjung Kim, Ryumduck Oh and Jeonghwan Gwak. "Enhanced White Blood Cell Classification via YOLO-based Region-of-Interest Extraction and Feature Ensemble" Journal of The Korea Society of Computer and Information 30, no.1 (2025) : 1-14.
