Deep Learning with MATLAB: Using Feature Extraction with Neural Networks in MATLAB
From the series: Deep Learning with MATLAB
Gabriel Ha, MathWorks
This demo uses MATLAB® to train a SVM classifier with features extracted, using a pretrained CNN for classifying images of four different animal types: cat, dog, deer, and frog. Images are used from the CIFAR-10 dataset (https://www.cs.toronto.edu/~kriz/cifar.html).
Product Focus
Recorded: 12 Apr 2017
Other Resources
Series: Deep Learning with MATLAB
Quick Start
Deep Learning in 11 Lines of MATLAB Code See how to use MATLAB, a simple webcam, and a deep neural network to identify objects in your surroundings. This demo uses AlexNet, a pretrained deep convolutional neural network that has been trained on over a million images.
Transfer Learning in 10 Lines of MATLAB Code Learn how to use transfer learning in MATLAB to re-train deep learning networks created by experts for your own data or task.
Tutorials
Training a Neural Network from Scratch with MATLAB Use MATLAB for configuring, training, and evaluating a convolutional neural network for image classification.
Transfer Learning with Neural Networks in MATLAB Use MATLAB for fine-tuning a pretrained convolutional neural network for image classification.
Using Feature Extraction with Neural Networks in MATLAB Use MATLAB for extracting features with a pretrained convolutional neural network and to train a support vector machine classifier for image classification.
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