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.
This course is part of the Mind and Machine Specialization
About this Course
What you will 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.
Syllabus - What you will learn from this course
Edges, Depth, and Objects
Machine Learning and Neural Networks
- 5 stars57.62%
- 4 stars30.50%
- 3 stars10.16%
- 1 star1.69%
TOP REVIEWS FROM COMPUTATIONAL VISION
Good understanding of mechanism of computer vision through deep learning
Very nice course but needs to include more instructiveness with lots of examples.
About the Mind and Machine Specialization
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