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Deep Learning ToolboxTM Model for ShuffleNet Network

Pretrained ShuffleNet model for image classification


Updated 16 Sep 2020

ShuffleNet is a pretrained model that has been trained on a subset of the ImageNet database. The model is trained on more than a million images and can classify images into 1000 object categories (e.g. keyboard, mouse, pencil, and many animals).

Opening the shufflenet.mlpkginstall file from your operating system or from within MATLAB will initiate the installation process for the release you have.

This mlpkginstall file is functional for R2019a and beyond.

Usage Example:

% Access the trained model
net = shufflenet ();

% See details of the architecture

% Read the image to classify
I = imread('peppers.png');

% Adjust size of the image
sz = net.Layers(1).InputSize
I = I(1:sz(1),1:sz(2),1:sz(3));

% Classify the image using shufflenet
label = classify(net, I)

% Show the image and the classification results

For additional information, please refer documentation:

Comments and Ratings (1)

Ziru Pan

I wanna look up the function: helperNnetShufflenetLayerChannelShufflingLayer to see how can it shuffles the inputs.
But "help helperNnetShufflenetLayerChannelShufflingLayer" or "open helperNnetShufflenetLayerChannelShufflingLayer" didn't work.

MATLAB Release Compatibility
Created with R2019a
Compatible with R2019a to R2020b
Platform Compatibility
Windows macOS Linux