Article

A Comparative Analysis of Lightweight Deep Learning Architectures for Malaria Cell Image Classification on Edge Devices

2026-01-08

Abstract excerpt

Malaria remains a significant global health burden, particularly in resource-limited regions where automated diagnostic tools are critically needed. This paper presents a comprehensive comparative analysis of lightweight deep learning architectures designed for malaria parasite detection from blood cell microscopy images, with emphasis on deployment on resourceconstrained edge devices. We evaluate five prominent l...

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Literature Corpus work: 44673889-d807-537d-a001-8b805f3541b9
DOI: 10.22541/au.176790715.56571253/v1

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