ResNet101v2

class ResNet101v2(noTop: Boolean, inputShape: IntArray?) : TFModels.CV<Functional>

This model is a neural network for image classification that take images as input and classify the major object in the image into a set of 1000 different classes (labels are available via org.jetbrains.kotlinx.dl.impl.dataset.Imagenet.V1k.labels method).

This model has 101 layers with ResNetv2 architecture.

The model have

an input with the shape (1x224x224x3)
an output with the shape (1x1000)

NOTE: ResNet v2 uses pre-activation function whereas ResNet v1 uses post-activation for the residual blocks.

NOTE: This model is converted from Keras.applications, the last few layers in the noTop model have been removed so that the user can fine-tune the model for his specific task.