Student Work

Machine Learning, Image Processing, and Transfer Learning for Handwritten Spreadsheet Digitization

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This report details the development of a software program aimed at converting handwritten parachute data records from the Natick Army Lab into an analyzable digital format. Due to the failure of traditional OCR models to recognize handwritten fractions, a crucial part of the data, we generated a synthetic dataset to specifically fine-tune these models. The software utilizes image processing and OCR technologies to translate text and replicate the physical document's layout in a digital format. This innovation streamlines data analysis, enhancing the Army's ability to monitor and understand parachute integrity and lifecycle.

  • This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.
Creator
Subject
Publisher
Identifier
  • E-project-041724-161231
  • 121155
Palavra-chave
Advisor
Year
  • 2024
Sponsor
UN Sustainable Development Goals
Date created
  • 2024-04-17
Resource type
Major
Source
  • E-project-041724-161231
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