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Using Machine Learning To Interpret Dice Rolls, Hunter Wimsatt, Aarohi Panzade, Kaaustaaub Shankar, Warren Campbell
Using Machine Learning To Interpret Dice Rolls, Hunter Wimsatt, Aarohi Panzade, Kaaustaaub Shankar, Warren Campbell
SEAS Faculty Publications
Gamers use polyhedral dice that come with 4 sides (D4), 6 sides (D6), 8 sides (D8), 10 sides (D10), 12 sides (D12) and 20 sides (D20). All dice are unfair, some more than others. The goal of this project was to develop a machine learning and computer vision solution for the interpretation of dice rolls. When combined with an automated dice roller it would facilitate the study of dice unfairness. In the machine learning literature, Convolutional Neural Networks (CNNs) are the preferred method of computer classification of images. The CNN convolves images with different weights and biases through multiple layers …