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Computational Vision

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.

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What's inside

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.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Explores models that address various vision tasks, including edges, depth, objects, and mental imagery, providing a comprehensive understanding of visual cognition

Taught by David Quigley, an experienced instructor recognized for his work in cognitive science and computational models of the mind

Examines the boundaries of visual cognition, leading to a more complex analysis of the mind and brain, enhancing students' understanding of cognitive processes

Introduces students to machine learning and neural networks, providing a foundation for understanding artificial intelligence and the implementation of these concepts in cognitive systems

Requires students to come in with a basic understanding of cognitive science or related fields, which may not be suitable for complete beginners

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Reviews summary

Engaging, detailed course on computer vision

Learners say that this engaging, detailed course gives a strong introduction to computational vision. Students appreciate its depth on machine learning and neural networks. The course covers parallels between computing and human vision, which learners find unique and insightful. Many recommend this course for learners who want to understand the fundamentals of computer vision.

Students found that the course instructor was excellent.

"The course instructor is excellent"

"Very nice lecturer"

Students generally found this course to be engaging.

"A great course, one I would certainly recommend!"

"engaging"

"detailed"

Many learners found the content of the course to be deep and engaging.

"very thorough and relevant"

"not too heavy on actual implementations"

"unconventional approach of linking concepts to how our eyes and brain perceive visual information more than makeup for it"

Students remarked that the course could be more up-to-date.

"the course appears as if it was created in the late 1990s and then superficially updated with bits of deep learning"

Students wished that the course had more challenging quizzes.

"Lack of help in quizzes makes it difficult"

"the quizzes need more questions and better guidance"

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Computational Vision with these activities:

Review: Artificial Intelligence: A Modern Approach, 4th Edition

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Review a standard text on the topic to build a foundation for the study of Computer Vision.

View Artificial Intelligence on Amazon

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Read the preface and Chapter 1
Summarize the key concepts in Chapter 1
Answer the review questions at the end of Chapter 1

Watch a video tutorial on neural networks

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A video tutorial can provide a quick and easy way to learn about a new topic.

Browse courses on Neural Networks

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Find a video tutorial on neural networks
Watch the tutorial and take notes
Try out the examples in the tutorial

Create a mind map of vision as a cognitive problem space

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Creating a mind map will help you visualize the key concepts and how they relate to each other.

Browse courses on Cognitive Science

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List the key concepts in the course description
Create a central node for each concept on a piece of paper
Draw lines between the nodes to show how they are related

Three other activities

Expand to see all activities and additional details

Show all six activities

Solve practice problems on edge detection and depth perception

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Practice problems will help you develop your problem-solving skills and deepen your understanding of the material.

Browse courses on Computer Vision

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Find practice problems online or in a textbook
Set aside some time to work on the problems
Check your answers and learn from your mistakes

Attend a workshop on computer vision

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A workshop can provide an opportunity to learn from experts and network with other professionals.

Browse courses on Computer Vision

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Find a workshop on computer vision
Register for the workshop
Attend the workshop and participate in the activities

Design a neural network to solve a simple computer vision problem

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Creating a neural network will help you apply your knowledge of neural networks to a real-world problem.

Browse courses on Neural Networks

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Choose a simple computer vision problem to solve
Design a neural network architecture to solve the problem
Implement the neural network in a programming language
Train the neural network on a dataset
Evaluate the performance of the neural network

Career center

Learners who complete Computational Vision will develop knowledge and skills that may be useful to these careers:

Computer Vision Engineer

A Computer Vision Engineer is a software engineer who specializes in developing computer vision systems. As a Computer Vision Engineer, you will work on a variety of different projects, from developing facial recognition systems to creating self-driving cars. Computational Vision can give you a strong foundation for this role, as it will teach you the fundamentals of computer vision and image processing.

See salaries and explore the career path for Computer Vision Engineer

Machine Learning Engineer

A Machine Learning Engineer is a person who designs and develops machine learning models. As a Machine Learning Engineer, you will work with a variety of different types of data to build models that can make predictions or recommendations. Computational Vision can help you build a solid foundation in this career by providing you with the skills and knowledge you need to develop computer vision models. You can also apply your understanding of machine learning to your work on vision systems, which can give you a competitive edge in the job market.

See salaries and explore the career path for Machine Learning Engineer

Perception Scientist

A Perception Scientist is a Scientist who studies how people perceive the world around them. As a Perception Scientist, you will explore how people see, hear, smell, taste, and touch. You can use your insights to develop new products or services that are more user-friendly or to improve existing ones. Computational Vision can provide you with essential knowledge about visual perception. This course will teach you advanced models to address the complex and challenging problems in perception.

See salaries and explore the career path for Perception Scientist

Robotics Engineer

A Robotics Engineer is an individual who designs, builds, programs, and maintains robots. As a Robotics Engineer, you are at the forefront of creating robots to solve some of the world's greatest challenges. Computational Vision can help you succeed in this career as it provides you with the critical understanding and skills to give the robots you design better vision capabilities. You will be able to tackle challenges in perception and cognition, such as object recognition, navigation, and planning. If you are interested in using Computational Vision to help robots perceive the world around them, then this is an important course for you.

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Artificial Intelligence Researcher

An Artificial Intelligence Researcher is a Scientist who develops new artificial intelligence algorithms and technologies. As an Artificial Intelligence Researcher, you will work on a variety of different projects, from developing new ways to process natural language to creating self-driving cars. Computational Vision can provide you with important knowledge on image processing, object recognition and machine learning, which are fundamental to developing AI systems.

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Data Scientist

A Data Scientist is a person who uses data to solve problems. As a Data Scientist, you will work with a variety of different types of data to identify trends and patterns. You can use your insights to develop new products or services or to improve existing ones. Computational Vision will help you succeed in this career as it gives you the ability to extract valuable information from images. This skill is in high demand in many different industries, such as retail, healthcare, and manufacturing.

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User Experience Designer

A User Experience Designer is a person who designs the user interface for websites and other digital products. As a User Experience Designer, you will work to create interfaces that are both visually appealing and easy to use. Computational Vision can improve your professional practice, as it will teach you how to use computer vision techniques to improve the user experience. You can use this knowledge to design interfaces that are more intuitive and responsive to user needs.

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Biomedical Engineer

A Biomedical Engineer is an Engineer who designs and develops medical devices and systems. As a Biomedical Engineer, you will work on a variety of different projects, from developing new ways to diagnose diseases to creating new treatments. Computational Vision can support your career by providing you with the skills and knowledge you need to develop computer vision systems for medical applications. This is a rapidly growing field, and there is a high demand for qualified Biomedical Engineers.

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Instructional Designer

An Instructional Designer is a person who designs and develops educational materials. As an Instructional Designer, you will work on a variety of different projects, from creating online courses to developing training materials for employees. Computational Vision can support your career if you want to incorporate interactive visual elements into your instructional materials. You will learn about the latest computer vision technologies and how to use them to create engaging and effective learning experiences.

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Cognitive Scientist

Cognitive Scientists study the mind and its processes. As a Cognitive Scientist, you will explore how people think, learn, and remember. You can use your insights to develop new educational programs or design new products that are more user-friendly. Studying Computational Vision may help you better understand how people perceive and process visual information. Such knowledge can refine how you approach research in human cognition or develop interfaces between humans and computers.

See salaries and explore the career path for Cognitive Scientist

Speech-Language Pathologist

A Speech-Language Pathologist is a healthcare professional who helps people with speech, language, and swallowing disorders. As a Speech-Language Pathologist, you will work with a variety of different patients, from children with autism to adults who have had a stroke. Computational Vision may give you an edge in your profession by allowing you to develop computer vision systems that can help diagnose and treat speech-language disorders.

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Digital Artist

A Digital Artist is an artist who creates digital images or animations. As a Digital Artist, you will work on a variety of different projects, from creating illustrations for websites to developing visual effects for movies. Computational Vision can aid your career by teaching you the fundamentals of image processing and computer vision. This knowledge can help you create more realistic and visually appealing images and animations.

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Human Factors Engineer

A Human Factors Engineer is an Engineer who designs products and systems that are safe and easy to use. As a Human Factors Engineer, you will work on a variety of different projects, from designing new cars to creating new medical devices. Computational Vision can help build a solid foundation in this career, as it provides you with the skills and knowledge you need to understand how people see and interact with the world around them.

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Neuroscientist

A Neuroscientist is a Scientist who studies the nervous system. This includes the brain, spinal cord, and peripheral nerves. As a Neuroscientist, you will work to understand how the different parts of the nervous system work together to control our thoughts, feelings, and actions. Computational Vision can help you succeed in this career through its deep dive into the cognitive problem space related to vision. You will be able to study how the brain processes visual information and use that knowledge to develop new treatments for neurological disorders.

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Neuropsychologist

A Neuropsychologist is a Psychologist who specializes in the relationship between the brain and behavior. As a Neuropsychologist, you lead the innovations for discovering how the human mind works and find ways to help people who might have trouble with their brains. Studying Computational Vision can serve as strong support for your foundational knowledge. Because, you can learn about how the human brain sees and processes the world around it, which can give you important clues to the impact of brain injuries or disorders on behavior.

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Reading list

We've selected 14 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Computational Vision.

Vision

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Has been around for a long time, but when it comes to computational vision, this is the classic textbook. While it will not be up to date on the latest trends in deep learning, it fantastic book to deeply understand the early stages of visual processing. A must-read for anyone who wants to understand the field from a computational perspective.

Vision: A Computational Investigation into the...

Paperback

Vision: A Computational Investigation into the...

Kindle Edition