Computational Vision

Instructor: David Quigley

Beginner Level • 8 hours to complete • Flexible Schedule

What You'll Learn

  • Apply various models of human and machine vision and discuss their limitations.
  • Demonstrate the geon model of object recognition and its limitations.
  • Argue the benefits and drawbacks of the symbolist and visualist perspectives of mental imagery.
  • Recognize the single layer and multi-layer perceptron neural network models of artificial intelligence.

Skills You'll Gain

Artificial Neural Networks
Deep Learning
Computer Graphics
Psychology
Computational Thinking
Image Analysis
Computer Vision
Artificial Intelligence and Machine Learning (AI/ML)

Shareable Certificate

Earn a shareable certificate to add to your LinkedIn profile

Outcomes

  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 4 modules in this course

This week we will explore some basic assumptions of a simple model of human vision.

This week we will explore models of higher-order tasks solved by the visual system.

This week we will compare and contrast different perspectives of how mental imagery relates to the visual system.

This week we will explore the neuron as an element of the human cognitive system and ways we can implement these pieces into neural network systems of artificial intelligence.