Project Efua: A user trained, mobile-first image classification AI
Date
2019-04
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Abstract
Machine learning and the development of Artificial Intelligence (AI) has grown nearly
exponentially over the past few years. However, growing fears over the nature of AI and the
use of user data by large companies has put an air of distrust over the ML community. This
makes it hard to collect more data with better user representation is needed to train more useful
and accurate models and creates a unique problem space that my project seeks to tackle. It raises
the question; how might researchers improve public understanding of AI while creating more
representative datasets? To this question I propose the solution, Project Efua; a user taught
mobile AI application meant to bridge the gap between the developer community and the wider
public.
Description
Applied project submitted to the Department of Computer Science, Ashesi University, in partial fulfillment of Bachelor of Science degree in Computer Science, April 2019
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Applied project
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Keywords
artificial intelligence (AI), mobile application, machine learning, data collection, image recognition