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Convolutional Neural Networks and Image Processing II

This is a continuation of the Convolutional Networks and Image Processing course, in which we will focus in more detail on data preprocessing and advanced deep learning techniques for image processing.
Level
Designed for participants with basic knowledge and experience
intermediate
Course length
1 day
Language
 cz  eu
Course code
KT22110124
Artificial intelligence (AI)
Category:
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Courses with lecturer

Term
Language
Place
Form
?
How and where the course takes place.
Price without VAT
N
Novinka
Open term
?
We will agree on a specific date together. This is a non-binding order.
Language
Place
online
Form
virtual classroom
?
Online training with a lecturer at a specific time.
Code of the course: KT22110124-0001
Price without VAT
4 990 Kč
N
Novinka
Open term
?
We will agree on a specific date together. This is a non-binding order.
Language
Place
online
Form
virtual classroom
?
Online training with a lecturer at a specific time.
Code of the course: KT22110124-0002
Price without VAT
4 990 Kč

Course description

In addition to classifications well known from the previous course, we will focus on segmentation, object detection and especially advanced applications of generative adversarial networks (GAN) such as resolution enhancement, noise removal and Deep fake generation.

Required knowledge

  • Basic knowledge of Python programming
  • High School Mathematics
  • Course-level knowledge of machine learning Introduction to Machine Learning
  • Course-level knowledge Convolutional neural networks and image processing

Course content

  • Architectures of neural networks for image processing (convolution, deconvolution, pooling, residual connection)
  • Large neural networks for image processing (VGG 16 and ResNet)
  • Image segmentation (U-net, object detection)
  • A practical example of image segmentation
  • Generative Adversarial Networks (GANs)
  • A practical example for image generation
  • Superresolution (Upsampling, a practical example of increasing image resolution using GAN)
  • A practical larger-scale project to predict real estate prices using a combination of tabular and image data

Lecturers

Jiří Materna
Jiří Materna

He is a machine learning specialist with experience in its applications in industry since 2007. Between 2008 and 2017, he worked at Seznam.cz, of which the last 7 years as head of the research department. He now works as a freelancer, offers the development of custom machine learning solutions, organizes the Machine Learning Prague conference and writes the ML Guru blog. 

Do you want this tailor-made course for your company?

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Previous courses

Do you want this tailor-made course for your company?

Contact us

News with the course

Náhledový obrázek novinky
Artificial intelligence (AI) 28. 8. 2024
The Practical Application of AI: Unilever Reduced Recruitment Time by 75%

Unilever is an international company with more than 155,000 employees. Company faced a time-consuming process of recruiting talent. The recruitment process involved manually sifting through thousands of resumes and many hours spent on interviews, which was inefficient and costly.

Náhledový obrázek novinky
Artificial intelligence (AI) 9. 7. 2024
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