This repo contains an App Designer app for training an image classification deep neural networks in MATLAB. Using this app, you can:

• 🖼️ Import, visualize, and augment data
• ⚡ Quickly transfer learn with the SqueezeNet pretrained network
• 🛠️ Modify pretrained networks for transfer learning with Deep Network Designer
• 📥 Import networks from the workspace
• 🔍 Explain predictions with explainability techniques like Grad-CAM and LIME
• 🧾 Generate MATLAB code for training an image classifier

You can also edit and customize the app code for your own task.

• MATLAB ® R2025a or later
• Deep Learning Toolbox™
• (Optional) Parallel Computing Toolbox™ to train models on GPU
• (Optional) Image Processing Toolbox™ to use the imageLIME interpretability function

Import data and apply standard augmentations.

Choose a pretrained model, edit or build a model in Deep Network Designer, or import a model from the workspace.

Train the model, predict on data, and try out interpretability techniques.

To open the app, run the opening function at the MATLAB command line.

ImageClassifer;

To modify the app, run appdesigner("ImageClassifier.mlapp").

Copyright 2026 The MathWorks, Inc.