Deep Learning Toolbox Model for ResNet-101 Network
Updated Wed, 15 Mar 2023 00:00:00 +0000
ResNet-101 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, has 347 layers in total, corresponding to a 101 layer residual network, and can classify images into 1000 object categories (e.g. keyboard, mouse, pencil, and many animals).
Opening the resnet101.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 R2017b and beyond.
% Access the trained model
net = resnet101();
% 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 Resnet-101
label = classify(net, I)
% Show the image and the classification results
MATLAB Release Compatibility
Platform CompatibilityWindows macOS Linux
Inspired: Pre-trained 3D ResNet-101
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