Computational Vision

Beginner Level
8 hours to complete
Flexible Schedule

David Quigley

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.

Develop Your Specialized Knowledge

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.