Administrative information

Title	Convolutional Neural Networks and Transformers for images
Duration	60 min
Module	B
Lesson Type	Tutorial
Focus	Technical - Deep Learning
Topic	Neural Networks

Keywords

Convolutional Neural Networks,Transformer networks,Computer Vision,

Learning Goals

Implementing and training a CNN and a Transformer for a computer vision problem from scratch
Comparing the performance of the two models

Expected Preparation

Learning Events to be Completed Before

Obligatory for Students

Optional for Students

None.

References and background for students:

None.

Recommended for Teachers

None.

Lesson Materials

Jupyter notebook

The materials of this learning event are available under CC BY-NC-SA 4.0.

Instructions for Teachers

Here the goal is to show the implementation steps of the transformer network for images. We also implement a basic CNN with a similar number of trainable parameters, so we can compare the performance of the CNN to the ViT model.

Outline

Duration (min)	Description
15	Training a simple convolutional neural network
35	Training a vision transformer (ViT) neural network
10	Comparing the performance of the two different approaches

More information

Click here for an overview of all lesson plans of the master human centred AI

Please visit the home page of the consortium HCAIM

Acknowledgements

The Human-Centered AI Masters programme was co-financed by the Connecting Europe Facility of the European Union Under Grant №CEF-TC-2020-1 Digital Skills 2020-EU-IA-0068.

The materials of this learning event are available under CC BY-NC-SA 4.0

The HCAIM consortium consists of three excellence centres, three SMEs and four Universities