Date of Award

Fall 2020

Document Type

Thesis

Supervisor

Mikhail Timofeev

Abstract

The present document explores the use of machine learning techniques, specifically supervised learning and classification. It applies those techniques to create a solution for a real world company that provides medical products and services to hospitals. This project will deal with streamlining the calibration of medical weighing scales. The developed application will use object detection and character recognition to identify and classify a digital image of a scale’s tag, and fill in a form with the corresponding data. The main reason for the need of this application is to avoid human errors and automate the collection of data from the scales.

Comments

BSc in IT Y3

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