Module: tf.compat.v1.keras.applications.nasnet

NASNet-A models for Keras.

NASNet refers to Neural Architecture Search Network, a family of models that were designed automatically by learning the model architectures directly on the dataset of interest.

Here we consider NASNet-A, the highest performance model that was found for the CIFAR-10 dataset, and then extended to ImageNet 2012 dataset, obtaining state of the art performance on CIFAR-10 and ImageNet 2012. Only the NASNet-A models, and their respective weights, which are suited for ImageNet 2012 are provided.

The below table describes the performance on ImageNet 2012:

Architecture Top-1 Acc Top-5 Acc Multiply-Adds Params (M)
NASNet-A (4 @ 1056) 74.0 % 91.6 % 564 M 5.3
NASNet-A (6 @ 4032) 82.7 % 96.2 % 23.8 B 88.9

Reference:

Functions

NASNetLarge(...): Instantiates a NASNet model in ImageNet mode.

NASNetMobile(...): Instantiates a Mobile NASNet model in ImageNet mode.

decode_predictions(...): Decodes the prediction of an ImageNet model.

preprocess_input(...): Preprocesses a tensor or Numpy array encoding a batch of images.