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Deep Learning Toolbox Model for SqueezeNet Network

Pretrained SqueezeNet model for image classification

49 Downloads

Updated 12 Sep 2018

SqueezeNet 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 squeezenet.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 R2018a and beyond.

Usage Example:

net = squeezenet()
net.Layers
plot(net)

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

% Crop image to the input size of the network
sz = net.Layers(1).InputSize
I = I(100:sz(1)+99, 100:sz(2)+99, 1:sz(3));

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

% Show the image and classification result
figure
imshow(I)
text(10, 20, char(label), 'Color', 'white' )

Comments and Ratings (2)

jianY xu

I want to create a special layer to add some special noise to the data. But my matlab version is 2017b, I don't have the example " gaussianNoiseLayer.m". That file should be located at (matlabroot, 'examples', 'nnet', 'main', 'gaussianNoiseLayer.m') in the matlab 2018b version.
I really want to know the coding structure of adding noise layer. If any kind-hearted person has installed the latest version of matlab, can you send a copy of this file to me? email: xjy1236@sina.com
thank you very much!!

adel adel

MATLAB Release Compatibility
Created with R2018a
Compatible with R2018a to R2018b
Platform Compatibility
Windows macOS Linux

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