application_inception_resnet_v2  R Documentation 
InceptionResNet v2 model, with weights trained on ImageNet
application_inception_resnet_v2(
include_top = TRUE,
weights = "imagenet",
input_tensor = NULL,
input_shape = NULL,
pooling = NULL,
classes = 1000,
classifier_activation = "softmax",
...
)
inception_resnet_v2_preprocess_input(x)
include_top 
Whether to include the fullyconnected
layer at the top of the network. Defaults to 
weights 
One of 
input_tensor 
Optional Keras tensor
(i.e. output of 
input_shape 
optional shape list, 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 string or callable. The activation function to
use on the "top" layer. Ignored unless 
... 
For backwards and forwards compatibility 
x 

Do note that the input image format for this model is different than for the VGG16 and ResNet models (299x299 instead of 224x224).
The inception_resnet_v2_preprocess_input()
function should be used for image
preprocessing.
A Keras model instance.
Inceptionv4, InceptionResNet and the Impact of Residual Connections on Learning(https://arxiv.org/abs/1512.00567)
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