Table 3 Accuracy and loss during training and validation
From: A comparative study of multiple neural network for detection of COVID-19 on chest X-ray
Best epoch | Training loss | Training accuracy | Validation loss | Validation accuracy | |
|---|---|---|---|---|---|
VGG16 | 21 | 0.0100 | 0.9990 | 0.0000e+00 | 1.0000 |
VGG19 | 22 | 0.0122 | 0.9994 | 0.0000e+00 | 1.0000 |
DenseNet121 | 20 | 6.1363e−09 | 1.0000 | 7.2103e−07 | 1.0000 |
Inception-ResNet-V2 | 9 | 0.0022 | 0.9993 | 0.0011 | 1.0000 |
InceptionV3 | 3 | 0.0472 | 0.9943 | 0.0554 | 0.9963 |
ResNet50 | 4 | 1.1188e−04 | 1.0000 | 0.0633 | 0.9982 |
Xception | 4 | 0.0430 | 0.9951 | 0.0325 | 0.9926 |