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Udacity

Computer Vision and Generative AI

via Udacity

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Overview

Learn how computers process and understand image data, then harness the power of the latest Generative AI models to create new images.

Syllabus

  • Introduction to Image Generation
    • In this lesson, you will define image generation and understand its relevance in AI and machine learning.
  • Computer Vision Fundamentals
    • Learn how computers see images and perform key image processing techniques using classic image processing techniques such as image transformation, noise reduction, and more.
  • Image Generation and GANs
    • Explore the landscape of Gen AI tools for Computer Vision and learn how they are evaluated. Learn what a generative adversarial network is and how it is utilized to generate images.
  • Transformer-Based Computer Vision Models
    • In this lesson, we will be exploring Vision Transformers and the architecture that makes them work. Along the way we will explore Vision Transformers like DALL-E, DINO, and SAM.
  • Diffusion Models
    • Learn the fundamentals of transformers. Then, get hands-on with the creation of a diffusion algorithm and work with Huggingface Diffusers to generate and work with images.
  • Project: AI Photo Editing with Inpainting
    • In this project, you will utilize Generative AI to take a famous painting and swap out the background with an image generated by Stable Diffusion.

Taught by

Giacomo Vianello, Chuyi Shang, Annabel Ng, Derek Xu and Nathaniel Haynam

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