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.
Computational Vision
Computational Vision
This course is part of Mind and Machine Specialization
Instructor: David Quigley
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67 reviews
Beginner level
No prior experience required
8 hours to complete
Flexible schedule
Learn at your own pace
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.
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Assessments
5 assignments
Taught in English
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This course is part of the Mind and Machine Specialization
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Showing 3 of 67
AM
Reviewed on May 29, 2021
Good understanding of mechanism of computer vision through deep learning
DH
Reviewed on Mar 14, 2021
Very nice course but needs to include more instructiveness with lots of examples.
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