Threat Detection with Computer Vision
Autor(a) principal: | |
---|---|
Data de Publicação: | 2023 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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 |
id |
RCAP_599cd1798a00c1c77a3c8b41e7f71a33 |
---|---|
oai_identifier_str |
oai:run.unl.pt:10362/152095 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
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:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:34:27Zoai:run.unl.pt:10362/152095Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:54:47.679248Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
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:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
|
_version_ |
1799138136055349248 |