Classroom course

Convolutional Networks Course for Object Recognition

Classroom course

Convolutional Networks Course for Object Recognition

Course Tab

Price

787 € + VAT

Duration

8 hours

Tongue

Italian/English

Qualification obtained

Certificate

Course code

AGSAI005

Convolutional Neural Networks (CNNs) are one of the algorithms of Deep Learning well renowned nowadays in computer vision and find application in many fields: from autonomous cars to drones, from medical diagnosis to support and treatment for visually impaired.

Who is it for?

The online course is aimed at:

programmers
graduate students who know programming

Prerequisites

Mandatory in order to partecipate:

have the basics of Machine Learning (eg learning supervised, neural networks, cost functions etc.)
learn about the construction of Machine Learning models with Python
know the fundamentals of Probability Theory

Objective

The aim of this course is to present the latest architectures and their application on concrete problems: facial recognition, segmentation and identification of objects.

Programma

1. CNN

1.1 Convolutional layer
1.2 Padding
1.3 Pooling layer
1.4 Strided Convolutions

2. Deep CNN models

2.1 ResNet
2.2 Inception
2.3 MobileNet
2.4 EfficientNet
2.5 Transfer Learning

3. Object Detection

3.1 Object Localization
3.2 Landmark Detection
3.3 Object Detection
3.4 YOLO
3.5 Semantic Segmentation
3.5 U-Net

4. Facial Recognition

4.1 One shot Learning
4.2 Siamese Network
4.3 Facial Check

Classroom and safety rules

For compliance with Covid safety regulations, the classroom will be equipped with special air filtering systems and participation will be limited to a maximum of 8 participants with a green pass. The course will be confirmed upon reaching the minimum number of 4 participants.