An optimised YOLOv4 deep learning model for efficient malarial cell detection in thin blood smear images
Background Malaria is a serious public health concern worldwide. Early and accurate diagnosis is essential for controlling the disease's spread and avoiding severe health complications. Manual examination of blood smear samples by skilled technicians is a time-consuming aspect of the convention...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Published: |
BMC
2024
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| Subjects: | |
| Online Access: | http://eprints.um.edu.my/45309/ https://doi.org/10.1186/s13071-024-06215-7 |
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