Color classification using machine learning

Project (M.S., Electrical and Electronic Engineering)--California State University, Sacramento, 2020.

Machine learning and artificial intelligence continue to be active research fields focused on real-world problems. Machine learning uses computers to make predictions based on the provided data set or previous experience. Using machine learning methods such as supervised and unsupervised learning, we can process large data and solve classification problems. In this project, we have applied supervised learning, which is the most often used task-driven classification type of machine learning. The main goal of our project is classification of different color shades using machine learning under ideal and different non-ideal conditions. In this project, we used a binary classification technique of supervised learning to classify different colors.