Deep Learning Image Classifier App

Overview

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.

Requirements

• 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

Using the App

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.

Get Started

Open the App

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

ImageClassifer;

Edit the App

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

Copyright 2026 The MathWorks, Inc.