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.
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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.