Automated Identification of Malaria-Infected Cells and Classification of Human Malaria Parasites Using a Two-Stage Deep Learning Technique

The gold standard for diagnosing malaria remains microscopic examination; however, its application is frequently impeded by the lack of a standardized framework that guarantees uniformity and quality, particularly in scenarios with limited resources and high volume. This study suggests a novel and h...

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Main Authors:	Dhevisha, Sukumarran, Ee, Sam Loh, Anis Salwa, Mohd Khairuddin, Romano, Ngui, Wan Yusoff, Wan Sulaiman, Indra, Vythilingam, Paul Cliff Simon, Divis, Khairunnisa, Hasikin
Format:	Article
Language:	en
Published:	IEEE 2024
Subjects:	R Medicine (General)
Online Access:	http://ir.unimas.my/id/eprint/46209/1/2024_Sukumarran%20et%20al_Automated_Identification_of_Malaria_EAAI.pdf http://ir.unimas.my/id/eprint/46209/ https://ieeexplore.ieee.org/document/10679101
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