Table 3 For each dataset, the sensitivity, specificity and accuracy of classification of both models are shown.
From: Artifact detection in fluorescence microscopy using convolutional autoencoder
Dataset | Sensitivity | Specificity | Accuracy | |||
|---|---|---|---|---|---|---|
CNN | CAE | CNN | CAE | CNN | CAE | |
2 | 49.5% | 88.7% | 100% | 99.7% | 88.2% | 97.1% |
3 | 40.2% | 95.9% | 100% | 100.0% | 84.5% | 98.9% |
4 | 62.3% | 98.4% | 100% | 96.8% | 93.8% | 97.0% |
5 | 66.1% | 100.0% | 100% | 85.9% | 98.1% | 86.7% |
6 | 16.0% | 88.0% | 100% | 98.2% | 97.2% | 97.9% |
Mean | 46.82% | 94.2% | 100% | 96.1% | 92.36% | 95.5% |
