Machine Learning Approaches for Early Detection of Malaria Using Microscopic Images

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dc.contributor.authorChukwuemeka Obi
dc.date.accessioned2026-07-18T14:57:45Z
dc.date.issued2024-01-01
dc.description.abstractThis research presents a convolutional neural network-based system for automated detection of malaria parasites in blood smear microscopic images, achieving 94.7% classification accuracy.en
dc.identifier.urihttps://dspace.scola.ng/handle/123456789/14
dc.language.isoen
dc.subjectMalaria Detection
dc.subjectMachine Learning
dc.subjectMedical Imaging
dc.titleMachine Learning Approaches for Early Detection of Malaria Using Microscopic Imagesen
dc.typethesis

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