Working on Computer Vision tasks is always exciting for me. During my carrier I was working with many different types of images and was solving many different problems related to them in the fields of biology, medicine, genetics, climatology and many more. Today I would like to tell you about one of the most extraordinary use cases I’ve ever worked on.
Explainable Artificial Intelligence, or XAI for short, is a set of tools that helps us understand and interpret complicated “black box” machine and deep learning models and their predictions. In my previous post I showed you a sneak peek of my newest package called sauron, which allows you to explain decisions of Convolutional Neural Networks. I am really glad to say that beta version of sauron is finally here!
Explainable Artificial Intelligence, or XAI for short, is a set of tools that helps us understand and interpret complicated “black box” machine and deep learning models and their predictions. Today I would like to show you a sneak peek of my newest package called sauron, which allows you to explain decisions of Convolutional Neural Networks.
Beside image classification, object detection and image segmentation are two of the most common computer vision tasks. Check out how to perform them in R using platypus package in a few lines of code.
