Introduction to Computer Vision

Coursera Courses ↗ · Coursera

Open Course on Coursera

Free to audit · Opens on Coursera

Introduction to Computer Vision

Coursera · Beginner ·📐 ML Fundamentals ·1mo ago
In the first course of the Computer Vision for Engineering and Science specialization, you’ll be introduced to computer vision. You'll learn and use the most common algorithms for feature detection, extraction, and matching to align satellite images and stitch images together to create a single image of a larger scene. Features are used in applications like motion estimation, object tracking, and machine learning. You’ll use features to estimate geometric transformations between images and perform image registration. Registration is important whenever you need to compare images of the same scene taken at different times or combine images acquired from different scientific instruments, as is common with hyperspectral and medical images. You will use MATLAB throughout this course. MATLAB is the go-to choice for millions of people working in engineering and science, and provides the capabilities you need to accomplish your computer vision tasks. You will be provided free access to MATLAB for the course duration to complete your work. To be successful in this course, it will help to have some prior image processing experience. If you are new to image data, it’s recommended to first complete the Image Processing for Engineering and Science specialization.
Watch on Coursera ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Related AI Lessons

Python Programming Course in Delhi
Learn Python programming with a practical course in Delhi, designed for beginners and students
Medium · Python
Choosing the Right Architecture: A Software Engineer’s Field Guide to Neural Networks
Learn to choose the right neural network architecture for your AI project and understand the key considerations involved
Medium · Data Science
Chandra OCR 2: When Open Source Reads What Others Miss
Improve text extraction from documents with Chandra OCR 2, an open-source solution that outperforms others in accuracy
Medium · Machine Learning
The hidden value of teaching ML to Non-ML teams
Teaching ML to non-ML teams can break knowledge silos and increase project success, making it a valuable investment for companies
Medium · Machine Learning
Up next
Computational Thinking with JavaScript 2: Model & Analyse
Coursera
Watch →