About this Course
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Flexible deadlines

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Intermediate Level

Basic programming skills & experience; familiarity with basic linear algebra, calculus & probability, and 3D co-ordinate systems & transformations

Approx. 10 hours to complete

English

Subtitles: English

What you will learn

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    Understand machine learning techniques used in computer vision

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    Classify letters, objects and scenes

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    Detect and recognize faces

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    Solve computer vision problems with deep learning

Skills you will gain

Deep LearningMatlabMachine LearningComputer ProgrammingComputer Vision

Course 4 of 4 in the

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Basic programming skills & experience; familiarity with basic linear algebra, calculus & probability, and 3D co-ordinate systems & transformations

Approx. 10 hours to complete

English

Subtitles: English

Syllabus - What you will learn from this course

Week
1
4 hours to complete

Introduction to Visual Recognition & Understanding

9 videos (Total 30 min), 2 readings, 2 quizzes
9 videos
Health Care & Visual Perception2m
Detection, Localization & Classification6m
Recognition7m
Product Identification30s
Recognition: Progress & Unsolved Problems3m
More Unsolved Problems & Gaps1m
Machine Learning in Computer Vision31s
Machine Learning: Past & Present1m
2 readings
Resources (Optional): Introduction to Visual Recognition & Understanding30m
REQUIRED- MATLAB and Deep Learning Onramp2h
1 practice exercise
Machine Learning for Computer Vision30m
Week
2
1 hour to complete

Early Techniques

5 videos (Total 8 min), 1 reading, 1 quiz
5 videos
Techniques: Before Deep Learning47s
Adaboost for Face Detection1m
Eigenfaces for Face Recognition2m
SVMs for Object Detection1m
1 reading
Resources (Optional): Early Techniques30m
1 practice exercise
Training Neural Network30m
Week
3
1 hour to complete

Deep Learning Overview

6 videos (Total 12 min), 1 reading
6 videos
Introduction to Deep Learning3m
Insight on Deep Learning48s
Convolutional Neural Networks2m
LSTM, RNN & ResNet1m
Generative Models2m
1 reading
Resources (Optional) Deep Learning Overview30m
Week
4
1 hour to complete

Deep Learning in Computer Vision: Applications

9 videos (Total 17 min), 2 readings
9 videos
Deep Learning: Key Applications2m
Face Detection & Recognition1m
Image Segmentation1m
Video Understanding1m
Future of Computer Vision1m
Human-Machine Interaction1m
Future Research Areas3m
Evolution of Computer Vision2m
2 readings
Resources (Optional): Deep Learning in Computer Vision: Applications30m
Visual Recognition & Understanding - Key Takeaways10m

Instructors

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Radhakrishna Dasari

Instructor
Department of Computer Science
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Junsong Yuan

Associate Professor and Director of Visual Computing Lab
Computer Science and Engineering

About University at Buffalo

The University at Buffalo (UB) is a premier, research-intensive public university and the largest, most comprehensive institution of the State University of New York (SUNY) system. UB offers more than 100 undergraduate degrees and nearly 300 graduate and professional programs....

About The State University of New York

The State University of New York, with 64 unique institutions, is the largest comprehensive system of higher education in the United States. Educating nearly 468,000 students in more than 7,500 degree and certificate programs both on campus and online, SUNY has nearly 3 million alumni around the globe....

About the Computer Vision Specialization

This specialization provides a foundation in the rapidly expanding research field of computer vision, laying the groundwork necessary for designing sophisticated vision applications. Learners explore the integral elements that enable vision applications, ranging from editing images to reading traffic signs in self-driving cars to factory robots navigating around human co-workers. Content includes image processing and state-of-the-art vision techniques, augmented by insights from top leaders in the computer vision field. Learners gain hands-on experience writing computer vision programs through online labs using MATLAB and supporting toolboxes. The specialization is taught in MATLAB* using computer vision and supporting toolboxes. Learners should have basic programming skills and experience (understanding of for loops, if/else statements), specifically in MATLAB (Mathworks provides the basics here: https://www.mathworks.com/learn/tutorials/matlab-onramp.html). Learners should also be familiar with the following: basic linear algebra (matrix vector operations and notation), 3D co-ordinate systems and transformations, basic calculus (derivatives and integration) and basic probability (random variables). To learn more, check out a video overview at https://youtu.be/OfxVUSCPXd0. * A free license to install MATLAB for the duration of the course is available from MathWorks....
Computer Vision

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

More questions? Visit the Learner Help Center.