Deep Learning Toolbox Model for AlexNet Network
Pretrained AlexNet network model for image classification
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11. Sep 2024
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AlexNet is a pretrained Convolutional Neural Network (CNN) that has been trained on approximately 1.2 million images from the ImageNet Dataset (http://image-net.org/index). The model has 23 layers and can classify images into 1000 object categories (e.g. keyboard, mouse, coffee mug, pencil).
Opening the alexnet.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 R2016b and beyond. Use alexnet instead of imagePretrainedNetwork if using a release prior to R2024a.
Usage Example:
% Access the trained model
[net, classes] = imagePretrainedNetwork("alexnet");
% See details of the architecture
net.Layers
% 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 AlexNet
scores = predict(net, single(I));
label = scores2label(scores, classes)
% Show the image and the classification results
figure
imshow(I)
text(10,20,char(label),'Color','white')
Kompatibilität der MATLAB-Version
Erstellt mit
R2016b
Kompatibel mit R2016b bis R2024b
Plattform-Kompatibilität
Windows macOS (Apple Silicon) macOS (Intel) LinuxKategorien
- Image Processing and Computer Vision > Computer Vision Toolbox > Recognition, Object Detection, and Semantic Segmentation >
- AI and Statistics > Deep Learning Toolbox > Get Started with Deep Learning Toolbox >
- AI and Statistics > Deep Learning Toolbox > Image Data Workflows >
- AI and Statistics > Deep Learning Toolbox > Function Approximation, Clustering, and Control > Function Approximation and Clustering > Define Shallow Neural Network Architectures >
Mehr zu Recognition, Object Detection, and Semantic Segmentation finden Sie in Help Center und MATLAB Answers
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