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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