AI Deep Learning for Advance Image Processing & Manipulation

Images are everywhere! We live in a time where images contain lots of information, which is sometimes difficult to obtain. This is why image pre-processing has become a highly valuable skill, applicable in many use cases. In this workshop, participants will learn to process, transform, and manipulate images at your will, even when they come in thousands. Participants will also learn to restore damaged images, perform noise reduction, smart-resize images, count the number of dots on a dice, apply facial detection, and much more, using scikit-image. After completing this workshop, you will be able to apply your knowledge to different domains such as machine learning and artificial intelligence, machine and robotic vision, space and medical image analysis, retailing, and many more. Take the step and dive into the wonderful world that is computer vision!

Module 1: Introducing Image Processing and scikit-image

  • Make images come alive with scikit-image
  • NumPy for images
  • Getting started with thresholding
  • Lab session
    • RGB to grayscale
    • Flipping out
    • Histograms
    • Apply global thresholding
    • When the background isn’t that obvious
    • Trying other methods
    • Apply thresholding

Module 2: Filters, Contrast, Transformation and Morphology

  • Jump into filtering
  • Contrast enhancement
  • Transformations
  • Morphology
  • Lab session
    • Edge detection
    • Blurring to reduce noise
    • What’s the contrast of this image?
    • Medical images
    • Aerial image
    • Let’s add some impact and contrast
    • Aliasing, rotating and rescaling
    • Enlarging images
    • Proportionally resizing
    • Improving thresholded image

Module 3: Image restoration, Noise, Segmentation and Contours

  • Image restoration
  • Noise
  • Superpixels & segmentation
  • Finding contours
  • Lab session
    • Let’s restore a damaged image
    • Removing logos
    • Reducing noise while preserving edges
    • Number of pixels
    • Superpixel segmentation
    • Contouring shapes

Module 4: Advanced Operations, Detecting Faces and Features

  • Finding the edges with Canny
  • Right around the corner
  • Face detection
  • Real-world applications
  • Lab session
    • Edges
    • Less edgy
    • Perspective
    • Less corners
    • Multiple faces
    • Segmentation and Defect detection

Module 5: Use Cases of Deep Learning for Advanced Image Processing

Module 6: Capstone Project

  • Presentation
  • Ice-breaking
  • Brainstorm
  • Lab session
  • Group discussion
  • Quiz
  • Questionnaire
  • Use case
  • Case study
  • Q&A

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