4 citations · 4 across the 4 of their papers we have counts for
3 papers · 1 filter
CoSWA-YOLOv12: Scale-Invariant Tiny Object Detection and Segmentation of Malaria Parasites
Ahmed Tahiru Issah, Carine Mukamakuza
Automated microscopy could widen access to malaria diagnosis in low-resource settings, but the deadliest species, P. falciparum, presents in its early ring stage as an object only…
On-Device Multi-Species Malaria Detection with Uncertainty-Calibrated Slide-Level Aggregation
Idaya Seidu, Ahmed Tahiru Issah, Charles B. Delahunt +1
Malaria remains a leading cause of mortality in resource-limited settings, where expert microscopists are scarce. Automated diagnosis based on microscopy images thus has strong pot…
SGMCE: Segment-Grounded Morphological Concept Explanation for Malaria Parasite Species Identification in Thick Blood Smears
Ahmed Tahiru Issah, Charles B. Delahunt, Carine Mukamakuza
Malaria diagnosis in endemic regions depends on species-level identification of Plasmodium parasites in thick blood smears, but deep learning detectors classify detections without…