A MobileNet classifier reaches about 93% accuracy on the CP-AnemiC conjunctival pallor dataset, and FP16 post-training quantization preserves accuracy while INT8 and INT4 degrade it sharply.
An unacceptably high burden of anaemia and its predictors among young women (15–24 years) in low and middle income countries; setback to sdg progress,
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Performance Analysis of Post-Training Quantization for CNN-based Conjunctival Pallor Anemia Detection
A MobileNet classifier reaches about 93% accuracy on the CP-AnemiC conjunctival pallor dataset, and FP16 post-training quantization preserves accuracy while INT8 and INT4 degrade it sharply.