Data Labeling tools for Computer Vision: a Review

Detalhes bibliográficos
Autor(a) principal: Reis, Pedro Miguel Lima de Sousa
Data de Publicação: 2022
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/135873
Resumo: Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data Science
id RCAP_a19fc2bcde4c3c6241be0cd0bb3fe285
oai_identifier_str oai:run.unl.pt:10362/135873
network_acronym_str RCAP
network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository_id_str 7160
spelling Data Labeling tools for Computer Vision: a ReviewReviewComputer VisionImage AnnotationData Labeling softwareSupervised Machine LearningMethodologies and ToolsDissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data ScienceLarge volumes of labeled data are required to train Machine Learning models in order to solve today’s computer vision challenges. The recent exacerbated hype and investment in Data Labeling tools and services has led to many ad-hoc labeling tools. In this review, a detailed comparison between a selection of data labeling tools is framed to ensure the best software choice to holistically optimize the data labeling process in a Computer Vision problem. This analysis is built on multiple domains of features and functionalities related to Computer Vision, Natural Language Processing, Automation, and Quality Assurance, enabling its application to the most prevalent data labeling use cases across the scientific community and global market.Henriques, Roberto André PereiraRUNReis, Pedro Miguel Lima de Sousa2022-04-05T14:26:08Z2022-04-012022-04-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/135873TID:202988155enginfo: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:RCAAP2024-03-11T05:14:11Zoai:run.unl.pt:10362/135873Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:48:32.706023Repositório 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 Data Labeling tools for Computer Vision: a Review
title Data Labeling tools for Computer Vision: a Review
spellingShingle Data Labeling tools for Computer Vision: a Review
Reis, Pedro Miguel Lima de Sousa
Review
Computer Vision
Image Annotation
Data Labeling software
Supervised Machine Learning
Methodologies and Tools
title_short Data Labeling tools for Computer Vision: a Review
title_full Data Labeling tools for Computer Vision: a Review
title_fullStr Data Labeling tools for Computer Vision: a Review
title_full_unstemmed Data Labeling tools for Computer Vision: a Review
title_sort Data Labeling tools for Computer Vision: a Review
author Reis, Pedro Miguel Lima de Sousa
author_facet Reis, Pedro Miguel Lima de Sousa
author_role author
dc.contributor.none.fl_str_mv Henriques, Roberto André Pereira
RUN
dc.contributor.author.fl_str_mv Reis, Pedro Miguel Lima de Sousa
dc.subject.por.fl_str_mv Review
Computer Vision
Image Annotation
Data Labeling software
Supervised Machine Learning
Methodologies and Tools
topic Review
Computer Vision
Image Annotation
Data Labeling software
Supervised Machine Learning
Methodologies and Tools
description Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data Science
publishDate 2022
dc.date.none.fl_str_mv 2022-04-05T14:26:08Z
2022-04-01
2022-04-01T00:00:00Z
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/10362/135873
TID:202988155
url http://hdl.handle.net/10362/135873
identifier_str_mv TID:202988155
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_ 1799138086869794816

Registros relacionados