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Table 5 Average performance of the baseline multi-class CNN and best trained models (CNN-LSTM) on test data before and after post-processing step

From: Deep learning-based detection of seedling development

Model Accuracy Error Sensitivity Specificity Precision False positive rate
Multi-class CNN (Before) 0.72 ± 0.29 0.28 ± 0.29 0.73  ± 0.19 0.94 ± 0.21 0.91 ± 0.13 0.8 ± 0.08
Multi-class CNN (After) 00.80 ± 0.19 0.20 ± 0.19 0.85 ± 0.13 0.93 ± 0.07 0.85 ± 0.14 0.07 ± 0.07
CNN-LSTM (Before) 0.84 ± 0.04 0.16 ± 0.04 0.83  ± 0.05 0.93 ± 0.06 0.86 ± 0.09 0.05 ± 0.05
CNN-LSTM (After) 0.90 ± 0.08 0.10 ± 0.07 0.87 ± 0.11 0.96 ± 0.03 0.88 ± 0.15 0.04 ± 0.04
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Plant Methods

ISSN: 1746-4811