MATLAB Deep Learning Image Classifier App

저자 Mike Croucher, February 27, 2026

24 회 조회 (최근 30일) | 0 좋아요 | 0 댓글

Mike's pick this week is the Deep Learning Image Classifier App by MathWorks Deep Learning Toolbox Team.

Most people who start learning about Deep Learning begin with image classification workflows. I certainly did! My first deep learning experiments involved cats, dogs, digits and tiny little pictures of clothes! 

The MATLAB Deep Learning Image Classifier is a free App Designer app for training 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

Its a great way to get started with deep learning workflows without worrying about the code; although the code is just a click away when you are ready for it. 

The short video below gives an example of the app in use. In this case, we start off with a pre-trained image classification network called Squeezenet. Squeezenet can classify images into 1000 object categories, such as keyboard, mouse, pencil, and many animals. It cannot, however, classify MathWorks swag!

Using a technique called Transfer Learning, we can adapt squeezenet to recognize the different types of MathWorks swag and the entire workflow can be done in the app.

This just scratches the surface of what this app can do! Since it is all available on GitHub, you can even adapt the app itself to cover workflows that haven't been considered yet.