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Computer Vision and Image Analysis

Rp500,000 Rp99,000

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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.

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.


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

Estimate Time : 12-16 hours

Module 1 Introduction

  • The Evolution of Computer Vision
  • Image Processing Basics
  • Lab

Module 2 Image Features and Classical Method

  • Thresholding
  • Clustering
  • Region Growing
  • Template Matching
  • Edges and Corners
  • Lab

Module 3 Object Classification and Detection

  • Viola-Jonas
  • HOG
  • Classical VS Deep
  • Deep Learning
  • Classifiers to Detectors
  • Object Proposal
  • CNN Object Detectors
  • Lab

Module 4 Deep Segmentation and Transfer Learning

  • Super-Pixels and Conditional Random Fields
  • Fully Convolutional Approaches
  • Deep Segmenters
  • Transfer Learning
  • Lab

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
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
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.

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Beginner, Intermediate





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