F-measure conveys the weighted harmonic mean of the precision and recall, and is defined as F−measure=2×Precision×RecallPrecision+Recall(14) where c is the number of classes, and TP, FP, and FN represent the number of true positives, false positives, and false negatives, respectively. TP indicates when the model predicts the ith class label as “(healthy colony)” and the ith ground truth class label is likewise “(healthy colony).” FP indicates when the model predicts the ith class label as “(healthy colony)” but the ith ground truth class label is “(unhealthy colony).” FN indicates when the model predicts the ith class label as “(unhealthy colony)” but the ith ground truth class label is “(healthy colony).”