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Table 3 Data distribution for training and testing the model

From: An optimised YOLOv4 deep learning model for efficient malarial cell detection in thin blood smear images

Database

Total number of images before augmentation

Training images

Number of testing imagesa

Number of training images before augmentation

Number of training images after augmentation

MP-IDB (Dataset A)

210

168 (80%)

1000

42 (20%)

Malaria Research Centre, UNIMAS (Dataset B)

472

–

–

472

  1. MP-IDB Malaria Parasite Image Database, UNIMAS Universiti Malaysia Sarawak
  2. aNo augmentation was performed on testing images