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Image Segmentation and Classification using Small Data: An Application on Friendly Statements - A Computer Vision and Document Intelligence Project
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 3.29 MB | Adobe PDF |
Autores
Orientador(es)
Resumo(s)
Insurance companies face significant challenges in managing numerous physical documents containing
critical information, resulting in considerable time and cost expenditures. Although Deep Learning
models offer a promising solution, their implementation costs and data privacy concerns restrict
widespread adoption, especially when dealing with confidential documents. This internship report
presents a novel approach to address these challenges by developing a lightweight computer vision
solution for accurately detecting and processing checkboxes from Portuguese friendly statements. The
key objective was to demonstrate the feasibility of achieving high accuracy without relying on
advanced Deep Learning techniques. By leveraging a small set of examples, we successfully extracted
checkbox information while mitigating the high computational requirements associated with
traditional Deep Learning models. The results highlight the practicality and cost-effectiveness of our
approach, offering insurance companies a viable solution to streamline document management,
enhance data security, and improve overall efficiency. This research contributes to the computer vision
field by providing valuable insights into alternative methodologies that can be adopted to overcome
the limitations of Deep Learning, facilitating broader accessibility and utilization among insurance
providers.
Descrição
Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data Science
Palavras-chave
Computer vision Deep Learning Image segmentation Classification Small data SDG 8 - Decent work and economic growth SDG 9 - Industry, innovation and infrastructure SDG 11 - Sustainable cities and communities SDG 17 - Partnerships for the goals