DSC Capstone2020

From Immersive Visualization Lab Wiki
Revision as of 10:12, 2 October 2020 by Jschulze (Talk | contribs)

Jump to: navigation, search

DSC 180 Capstone Domain: Explainable AI (Section A01)

This page is under Construction and should be completed by the end of day on 10/4/2020

Overview

In this capstone domain we are going to study how we can make machine learning systems more user friendly by exploiting additional knowledge we can derive from the system and present it to the user. These types of systems are called Explainable AI.

The example we are going to use in this class is object recognition in images. We are first going to go over the basics of CNNs, then learn about saliency and attention maps, and finally we are going to implement the Grad-CAM algorithm in PyTorch and apply it to the COCO image data set.