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

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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.

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.

Course Tab


Price
787 € + VAT

Duration
8 hours

Tongue
Italian/English

Qualification obtained
Certificate

Course code
AGSAI005

REQUEST INFORMATION