DEV290X Computer Vision and Image Analysis
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.
- Working knowledge of Python
- Skills equivalent to the following courses
- DAT263x: Introduction to AI
- DAT236x: Deep Learning Explained