SISC: DEV290x Computer Vision and Image Analysis

Computer Vision and Image Analysis


SISC
Enrollment in this course is by invitation only

About this course

Computer Vision is the art of distilling actionable information from images.

In this hands-on course, we'll learn about Image Analysis techniques using OpenCV and the Microsoft Cognitive Toolkit to segment images into meaningful parts. We'll explore the evolution of Image Analysis, from classical to Deep-Learning techniques.

We'll use Transfer Learning and Microsoft ResNet to train a model to perform Semantic Segmentation.

Please Note: Learners who successfully complete this course can earn a CloudSwyft digital certificate and skill badge - these are detailed, secure and blockchain authenticated credentials that profile the knowledge and skills you’ve acquired in this course.

What you'll learn

  • Apply classical Image Analysis techniques, such as Edge Detection, Watershed and Distance Transformation as well as K-means Clustering to segment a basic dataset.
  • Implement classical Image Analysis algorithms using the OpenCV library.
  • Compare classical and Deep-Learning object classification techniques.
  • Apply Microsoft ResNet, a deep Convolutional Neural Network (CNN) to object classification using the Microsoft Cognitive Toolkit.
  • Apply Transfer Learning to augment ResNet18 for a Fully Convolutional Network (FCN) for Semantic Segmentation.

Prerequisites

  • Working knowledge of Python
  • Skills equivalent to the following courses
    • DAT263x: Introduction to AI
    • DAT236x: Deep Learning Explained

Meet the instructors

Andrew Byrne

Andrew Byrne

Senior Content Developer Microsoft Corporation

Andrew is a Senior Content Developer at Microsoft. His passion for software and teaching comes from 20+ years of software development experience at Microsoft, Siemens, Ericsson and his own startup.

Ivan Griffin, PhD

Ivan Griffin, PhD

Founder Emdalo Technologies, Ltd.

Ivan Griffin is a director and founder of Emdalo Technologies, where he works on developing embedded machine learning solutions. Ivan has over 20 years of experience in the embedded and semiconductor industries. He has a strong technical background combined with commercial and strategic understanding, and a proven track record in a number of successful start-ups. He has co-authored one patent application in computer vision, and two European and US patents in digital broadcast radio. Ivan has a Bachelor's (1995) and Master's degree in Electronic/Computer Engineering (1997) and Ph.D. (2010) in Computer Science from the University of Limerick, Ireland.

Daire McNamara

Daire McNamara

Founder Emdalo Technologies, Ltd.

An engineer by training, Daire co-founded Emdalo Technologies in 2013 with Dr. Ivan Griffin to realize Machine Learning at the Edge. Daire has over 20 years' experience in the high-tech electronics industries, having held senior commercial, management and product development roles in start-up and early phase companies targeting US, Asia-Pacific and European markets.

  1. Course Number

    DEV290x

  2. Classes Start

  3. Classes End

  4. Estimated Effort

    Total 12 to 16 hours