Computational Vision
Offered By: University of Colorado Boulder via Coursera
Course Description
Overview
In this course, we will expand on vision as a cognitive problem space and explore models that address various vision tasks. We will then explore how the boundaries of these problems lead to a more complex analysis of the mind and the brain and how these explorations lead to more complex computational models of understanding.
Syllabus
- Introduction
- This week we will explore some basic assumptions of a simple model of human vision.
- Edges, Depth, and Objects
- This week we will explore models of higher-order tasks solved by the visual system.
- Mental Imagery
- This week we will compare and contrast different perspectives of how mental imagery relates to the visual system.
- Machine Learning and Neural Networks
- 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.
Taught by
David Quigley
Tags
Related Courses
Neural Networks for Machine LearningUniversity of Toronto via Coursera Good Brain, Bad Brain: Basics
University of Birmingham via FutureLearn Statistical Learning with R
Stanford University via edX Machine Learning 1—Supervised Learning
Brown University via Udacity Fundamentals of Neuroscience, Part 2: Neurons and Networks
Harvard University via edX