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Table 3 Accuracy of the classification

From: Detecting spikes of wheat plants using neural networks with Laws texture energy

  Training Testing Validation Total
Spike samples (pixels) 13,372 2890 2779 19,041
Leaf samples (pixels) 53,265 11,389 11,500 76,154
TP ratea (%) 80.2 79 78.8 79.9
TN ratea (%) 95.7 95.6 95.9 95.7
Accuracya(%) 92.5 92.3 92.4 92.4
  1. aAccuracy, TP rate and TN rate were defined as follows:
  2. \(Accuracy = \frac{TP + TN}{TP + FP + TN + FN}\); \(Tprate = \frac{TP}{TP + FN}\); \(TNrate = \frac{TN}{FP + TN}\)
  3. where TP, TN, FP, and FN represent the numbers of true positives, true negatives, false positives, and false negatives, respectively