| [72] |
[18], [65], [22]
|
InceptionV3 |
| Deep-COVID [28]
|
[18], [66]
|
ResNet18, ResNet50, SqueezeNet, DenseNet121 |
| [73] |
[18], [23]
|
Bayesian ResNet50V2 |
| [74] |
[18], [22], [66], [68], [66], [64]
|
VGG 16, InceptionV3, Xception, DenseNet121, NASNet-mobile |
| [31] |
[18], [23]
|
CapsNet |
| [26] |
[18], [22]
|
ResNet18 |
| DeTraC [36]
|
[18], [63]
|
AlexNet, ResNet18 |
| [75] |
[18], [64]
|
ResNet50V2, Xception |
| [51] |
[18], [64], [65], [19], [23]
|
AOCT-Net, MobileNet, ShuffleNet |
| [34] |
[18]
[23]
|
AlexNet, SqueezeNet, GoogLeNet, VGG, MobileNet, ResNet18, ResNet50, ResNet101, DenseNet |
| [53] |
[18], [64]
|
Autoencoders, ResNet18 |
| [76] |
[18], [65], [23]
|
DenseNet161 |
| [57] |
[23] |
ResNet152 |
| [41] |
[18], [20]
|
VGG16, VGG19, InceptionResNetV2, InceptionV3, Xception |
| [6] |
[18], [69]
|
RestNet50 |
| [77] |
Locally collected from Hospital San Gerardo, Monza, Italy, and IRCCS Policlinico San Donato, Italy |
RestNet10 |
| [46] |
[18] |
VGG19, DenseNet121, InceptionV3, ResNetV2, Inception, ResNet-V2, Xception, MobileNetV2 |
| [35] |
[18], (Winner of the COVID-19 Dataset Award) [21]
|
AlexNet, DenseNet201, GoogleNet, InceptionV3, ResNet18, ResNet50, ResNet101, VGG16, VGG19, XceptionNet, InceptionResNetV2 |
| [44] |
[18], [65], [69]
|
ResNet50, VGG16 |
| [27] |
[18], [23]
|
ResNet50, InceptionV3, InceptionResNetV2 |
| [79] |
[20] |
SqueezeNet |
| [66] |
DenseNet121 |
| [80] |
[20] |
DenseNet121 |
| [42] |
[18]
[23]
|
VGG16, VGG19, ResNet50, ResNet50V, ResNet101, ResNet101V2, ResNet152, ResNet152V2, DenseNet121, DenseNet169, DenseNet201, MobileNetV1, XeptionNet, InceptionV3, InceptionResNetV2 |
| [82] |
[18] |
CNN |
