application_densenet201 | R Documentation |
Instantiates the Densenet201 architecture.
application_densenet201(
include_top = TRUE,
weights = "imagenet",
input_tensor = NULL,
input_shape = NULL,
pooling = NULL,
classes = 1000L,
classifier_activation = "softmax"
)
include_top |
whether to include the fully-connected layer at the top of the network. |
weights |
one of |
input_tensor |
optional Keras tensor
(i.e. output of |
input_shape |
optional shape tuple, only to be specified
if |
pooling |
Optional pooling mode for feature extraction
when
|
classes |
optional number of classes to classify images
into, only to be specified if |
classifier_activation |
A |
A Keras model instance.
Densely Connected Convolutional Networks (CVPR 2017)
Optionally loads weights pre-trained on ImageNet.
Note that the data format convention used by the model is
the one specified in your Keras config at ~/.keras/keras.json
.
Each Keras Application expects a specific kind of input preprocessing.
For DenseNet, call application_preprocess_inputs()
on your inputs before passing them to the model.
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