| model_vgg | R Documentation | 
VGG models implementations based on Very Deep Convolutional Networks For Large-Scale Image Recognition
model_vgg11(pretrained = FALSE, progress = TRUE, ...)
model_vgg11_bn(pretrained = FALSE, progress = TRUE, ...)
model_vgg13(pretrained = FALSE, progress = TRUE, ...)
model_vgg13_bn(pretrained = FALSE, progress = TRUE, ...)
model_vgg16(pretrained = FALSE, progress = TRUE, ...)
model_vgg16_bn(pretrained = FALSE, progress = TRUE, ...)
model_vgg19(pretrained = FALSE, progress = TRUE, ...)
model_vgg19_bn(pretrained = FALSE, progress = TRUE, ...)
pretrained | 
 (bool): If TRUE, returns a model pre-trained on ImageNet  | 
progress | 
 (bool): If TRUE, displays a progress bar of the download to stderr  | 
... | 
 other parameters passed to the VGG model implementation.  | 
model_vgg11(): VGG 11-layer model (configuration "A")
model_vgg11_bn(): VGG 11-layer model (configuration "A") with batch normalization
model_vgg13(): VGG 13-layer model (configuration "B")
model_vgg13_bn(): VGG 13-layer model (configuration "B") with batch normalization
model_vgg16(): VGG 13-layer model (configuration "D")
model_vgg16_bn(): VGG 13-layer model (configuration "D") with batch normalization
model_vgg19(): VGG 19-layer model (configuration "E")
model_vgg19_bn(): VGG 19-layer model (configuration "E") with batch normalization
Other models: 
model_alexnet(),
model_inception_v3(),
model_mobilenet_v2(),
model_resnet
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