Threat Detection with Computer Vision

Detalhes bibliográficos
Autor(a) principal: Cardoso, Gabriel Azenha
Data de Publicação: 2023
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: http://hdl.handle.net/10362/152095
Resumo: Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business Analytics
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spelling Threat Detection with Computer Visioncomputer visiondeep learninginferencesecurityInternship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business AnalyticsThis document describes the work conducted during an internship experience at the AI Innovation Department of Everis UK (now NTT Data). It reports what was done, learned, and developed with the sole objective of having a commercial product solution for the company's clients. The primary goal was to implement a solution in retail stores, to help assist the security team with threat detection. To do so, the solution consists in deploying trained deep learning models into hardware connected to the CCTV security cameras and detecting in that live feed any potential threats. By the time I started working on this project, was at an advanced stage so I had to study all the work previously done to understand what was needed and properly integrate the team fully. My contribution was focused on the model training process, where I had to create and structure a dataset and train a model capable of detecting the targeted classes quickly and accurately.Castelli, MauroRUNCardoso, Gabriel Azenha2023-04-24T14:04:04Z2023-04-102023-04-10T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/152095TID:203268393enginfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-22T18:11:03Zoai:run.unl.pt:10362/152095Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:41:21.308735Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Threat Detection with Computer Vision
title Threat Detection with Computer Vision
spellingShingle Threat Detection with Computer Vision
Cardoso, Gabriel Azenha
computer vision
deep learning
inference
security
title_short Threat Detection with Computer Vision
title_full Threat Detection with Computer Vision
title_fullStr Threat Detection with Computer Vision
title_full_unstemmed Threat Detection with Computer Vision
title_sort Threat Detection with Computer Vision
author Cardoso, Gabriel Azenha
author_facet Cardoso, Gabriel Azenha
author_role author
dc.contributor.none.fl_str_mv Castelli, Mauro
RUN
dc.contributor.author.fl_str_mv Cardoso, Gabriel Azenha
dc.subject.por.fl_str_mv computer vision
deep learning
inference
security
topic computer vision
deep learning
inference
security
description Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business Analytics
publishDate 2023
dc.date.none.fl_str_mv 2023-04-24T14:04:04Z
2023-04-10
2023-04-10T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/152095
TID:203268393
url http://hdl.handle.net/10362/152095
identifier_str_mv TID:203268393
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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