Transfer Learning

version 2019.6.2 (1.17 MB) by Kevin Chng
Transfer Learning of Pre-trained Neural Network or Imported ONNX Classification Model in GUI


Updated 5 Nov 2019

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It allows user to do transfer learning of pre-trained neural network, imported ONNX classification model or imported MAT file classification model in GUI without coding. Other than using the existing model, user can design their neural network using Deep Network Designer (MATLAB built-in application) and later use this app to train the neural network. User can analyze the pre-trained network or imported network in this app. It also allows user to modify the image augmenter information and training option (hyperparameters). Once completed the training of network, user may export the trained network to workspace, MAT file, ONNX file and generate MATLAB code for the steps being done in the application. User can generate NVIDIA GPU CUDA Code, however it is not supporting imported ONNX model.

Pre-trained Neural Network available :
1) alexnet
2) googlenet(ImageNet)
3) goolgenet(Places365)
4) resnet18
5) resnet50
6) resnet101
7) vgg16
8) vgg19
9) inceptionv3
10) inceptionresnetv2
11) squeezenet
12) densenet201
13) mobilenetv2
14) shufflenet
16) xception
17) nasnetmobile
18) nasnetlarge
19) import ONNX model
20) import mat file model

[Up to R2019a, imported ONNX layer is not supporting generation of CUDA code]

How to design & train neural network using this app?

How to import ONNX Model to train using this app?

Cite As

Kevin Chng (2022). Transfer Learning (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2019b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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