MediScan AI: A Computer Vision and Deep Learning-Based Application

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dc.contributor.authorChaudhari, Somita
dc.contributor.authorBrown, Tiffany
dc.date.accessioned2026-01-22T16:19:16Z
dc.date.issued2025-11-15
dc.descriptionIEEE Baltimore Technical Colloquium, Baltimore, Maryland, United States, November 15, 2025
dc.description.abstractThis project presents a deep learning-based pill recognition system that uses Convolutional Neural Networks (CNNs) to identify pharmaceutical pills from images with over 90% accuracy. A Streamlit-powered web application operationalizes this model, enabling users, including pharmacists, patients, and supply chain professionals to verify pills in real time using uploaded images.
dc.format.extent1 page
dc.genreconference papers and proceedings
dc.genrepreprints
dc.identifierdoi:10.13016/m2fevf-a5kk
dc.identifier.urihttp://hdl.handle.net/11603/41564
dc.language.isoen
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Information Systems Department
dc.relation.ispartofUMBC Student Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.titleMediScan AI: A Computer Vision and Deep Learning-Based Application
dc.typeText

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