Inception-ResNet 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 ) inception_resnet_v2_preprocess_input(x)
whether to include the fully-connected layer at the top of the network.
optional Keras tensor to use as image input for the model.
optional shape list, only to be specified if
Optional pooling mode for feature extraction when
optional number of classes to classify images into, only to be
Input tensor for preprocessing
A Keras model instance.
Do note that the input image format for this model is different than for the VGG16 and ResNet models (299x299 instead of 224x224).
inception_resnet_v2_preprocess_input() function should be used for image
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning(https://arxiv.org/abs/1512.00567)