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.
![](https://datascienceguts.com/images/sauron_beta/rsz_hexsticker_sauron.png)
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!
![](https://datascienceguts.com/images/sauron_sneak_peek/sauron_rgb.png)
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.
![](https://datascienceguts.com/images/hexsticker_platypus.png)
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.