Deep Learning for Image Processing: From the theory to the Industry 4.0

What you will learn

• Understand how a neural network learns and what it needs to learn well.

• Tune your neural network and use the right techniques to solve common problems that occur in real industrial applications to ensure better performance.

• Convolutional Neural Networks CNN and how they are used for image classification, object detection in images, and image segmentation.

• Several industrial use cases and examples will be presented all along the course for a better understanding of real applications.

Syllabus

Chapter 1: Introduction to Machine Learning

• What is Machine Learning?

• Machine Learning and statistics

• Types of Machine Learning models

Chapter 2: Introduction to Neural Networks

• Differences between Machine Learning and Deep Learning

• What is a Neural Network? and how does it learn?

Chapter 3: Convolutional Neural Networks

• Introduction to convolutional neural networks

• Structure and advantages of a convolutional neural network

Chapter 4: Training a neural network

• Preparing the dataset and its annotation

• Convergence and overfitting: Is my network learning well?

Chapter 5: Training tips and tricks

• Training techniques: Common problems during the training and how to solve them

Chapter 6: Convolutional Neural Network for Object Detection

• From Classification to Object Detection: an overview

Chapter 7: Convolutional Neural Network for Segmentation

• From Classification to Segmentation: an overview

Prerequisites

• Basic knowledge in mathematics and algebra 

• Basic level in English

• A PC and notebook

Target learners

Anyone wishing to acquire a specialization as a Deep Learning Engineer for image processing

Duration

32 hours in 2 months

Teaching mode: Hybrid

Start date: Saturday, 03 December 2022

End date: Saturday, 28 January 2023

Professor in charge

Prof. Karim Tout

Karim TOUT is the Head of AI at uqudo specializing in computer vision and digital identity. He has several years of experience leading AI teams and building AI-based computer vision products across diverse industries. He also provides expert consultancy and professional training on AI at Cetim France and teaches an AI Master course at the French-Azerbaijani University (UFAZ) as an invited professor.