Table 7 in An optimised YOLOv 4 deep learning model for efficient malarial cell detection in thin blood smear images

Table 7 Detection of infected red blood cells on Dataset A using the original YOLOv4 and modified models ModificationsModelPrecision (%)Recall rate (%)F1-score (%)mAP (%)Training time (h)Inference time (per image) (ms)B-FLOPSSize (MB)OriginalYOLOv484958993.8748726.6659.57244.40Residual block pruningYOLOv4-RC384928891.6535678.5347.59242.40YOLOv4-RC483928792.8437703.8251.21233.20YOLOv4-RC585898792.4737704.4857.61222.10YOLOv4-RC3_483898688.0932676.1837.35221.50YOLOv4-RC3_577777776.5632.5680.0145.64220.4Backbone replacementYOLOv4- ResNet-50L70847679.7028719.5037.33209.30YOLOv4- ResNet-50 M74868081.4328884.8237.33209.30 B-FLOPS Billion floating point operations, F1-SCoRE balance between precision and recall, mAP mean average precision