From the course: OpenCV for Python Developers
Join today to access over 24,400 courses taught by industry experts.
Additional techniques
From the course: OpenCV for Python Developers
Additional techniques
- [Instructor] From a computer vision standpoint, we have only scratched the surface with the topics covered so far. Let's take a moment to briefly look at some other algorithms in the field. One of those applications we've already seen briefly under the hood is machine learning. Specifically, we've been looking at supervised machine learning. This is a form of machine-based learning where you train a classifier using already tagged or identified data. For example, you start a pool of images that is an apple, and then a pool of images which are not an apple, The classifier then builds a little test, extracting features from the image, and for each of those tests, it is evaluated of how well it indicates it being one image object or another. When it comes to supervised machine learning, an important concept is the confusion matrix. The idea is that you can evaluate the effectiveness of your classifier or machine learned…
Practice while you learn with exercise files
Download the files the instructor uses to teach the course. Follow along and learn by watching, listening and practicing.
Download courses and learn on the go
Watch courses on your mobile device without an internet connection. Download courses using your iOS or Android LinkedIn Learning app.
