Project Efua: A user trained, mobile-first image classification AI

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dc.contributor.authorWoode, Ariel Arman
dc.date.accessioned2019-11-14T13:24:22Z
dc.date.available2019-11-14T13:24:22Z
dc.date.issued2019-04
dc.descriptionApplied project submitted to the Department of Computer Science, Ashesi University, in partial fulfillment of Bachelor of Science degree in Computer Science, April 2019en_US
dc.description.abstractMachine 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.en_US
dc.description.sponsorshipAshesi Universityen_US
dc.identifier.urihttp://hdl.handle.net/20.500.11988/463
dc.language.isoen_USen_US
dc.subjectartificial intelligence (AI)en_US
dc.subjectmobile applicationen_US
dc.subjectmachine learningen_US
dc.subjectdata collectionen_US
dc.subjectimage recognitionen_US
dc.titleProject Efua: A user trained, mobile-first image classification AIen_US
dc.typeApplied projecten_US

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