Computer Vision for Engineering and Science

Overview

Syllabus

Courses

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  11 hours 53 minutes

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  In the second course of the Computer Vision for Engineering and Science specialization, you will perform two of the most common computer vision tasks: classifying images and detecting objects. You will apply the entire machine learning workflow, from preparing your data to evaluating your results. By the end of this course, you’ll train machine learning models to classify images of street signs and detect material defects. 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 specialization, 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.
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  8 hours 18 minutes

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  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.
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  13 hours 46 minutes

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  In the third and final course of the Computer Vision for Engineering and Science specialization, you will learn to track objects and detect motion in videos. Tracking objects and detecting motion are difficult tasks but are required for applications as varied as microbiology and autonomous systems. To track objects, you first need to detect them. You’ll use pre-trained deep neural networks to perform object detection. You’ll also use optical flow to detect motion and use the results to detect moving objects. At the end of this course, you’ll apply all the skills learned in this specialization to a final project. You’ll take the role of an engineer being asked to track cars on a busy highway with the added challenge of counting each vehicle and its direction. 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 specialization, 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.

Taught by

Amanda Wang, Brandon Armstrong, Isaac Bruss, Matt Rich and Megan Thompson