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Microsoft: DEV290x Computer Vision and Image Analysis

Computer Vision and Image Analysis


A deep dive into Computer Vision, Image Analysis and Semantic Segmentation using the Microsoft Cognitive Toolkit.

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About this course

This course is part of the Microsoft Professional Program in Artificial Intelligence.

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.

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
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