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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Identifier8JMKD3MGPEW34M/47LTDJ5
Repositorysid.inpe.br/sibgrapi/2022/09.22.22.53
Last Update2022:09.26.21.36.08 (UTC) fred_s0@yahoo.com.br
Metadata Repositorysid.inpe.br/sibgrapi/2022/09.22.22.53.54
Metadata Last Update2023:05.23.04.20.43 (UTC) administrator
DOI10.1109/SIBGRAPI55357.2022.9991806
Citation KeyOliveiraCaCaSoCâQu:2022:PuDaFa
TitlePTL-AI Furnas Dataset: A Public Dataset for Fault Detection in Power Transmission Lines Using Aerial Images
Short TitlePTL-AI Furnas Dataset: A Public Dataset for Fault Detection in Power Transmission Lines Using Aerial Images
FormatOn-line
Year2022
Access Date2024, May 19
Number of Files1
Size15888 KiB
2. Context
Author1 Oliveira, Frederico Santos de
2 Carvalho, Marcelo de
3 Campos, Pedro Henrique Tancredo
4 Soares, Anderson da Silva
5 Cândido Júnior, Arnaldo
6 Quirino, Ana Cláudia Rodrigues da Silva
Affiliation1 Universidade Federal de Mato Grosso (UFMT)
2 Eletrobras-Furnas
3 Eletrobras-Furnas
4 Universidade Federal de Goiás (UFG)
5 Universidade Estadual Paulista (UNESP)
6 Eletrobras-Furnas
e-Mail Addressfred_s0@yahoo.com.br
Conference NameConference on Graphics, Patterns and Images, 35 (SIBGRAPI)
Conference LocationNatal, RN
Date24-27 Oct. 2022
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2022-09-26 21:36:08 :: fred_s0@yahoo.com.br -> administrator :: 2022
2023-05-23 04:20:43 :: administrator -> :: 2022
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Keywordsobject detection
power transmission lines
fault detection
AbstractWe present a new images dataset called PTL-AI Furnas Dataset as a new benchmark for fault detection in power transmission lines. This dataset has 6,295 images, with resolution 1280×720, extracted from the maintenance process of the energy transmission lines at Furnas company. It contains annotations of 17,808 components classified as baliser, bird nest, insulator, spacer and stockbridge. Furnas is a company that generates or transmits electricity to 51% of households in Brazil and more than 40% of the nations electricity passes through their grid enabling generating the dataset in different backgrounds and climatic conditions. We performed experiments using data augmentation techniques to train Faster R-CNN, Single-Shot Detects (SSD) and YoloV5 models. The benchmark result was obtained using the metrics of Mean Average Precision (mAP) and the Mean Average Recall (mAR) with values mAP=91.9% and mAR=89.7%. The PTL-AI Furnas Dataset is publicly available at https://github.com/freds0/PTL-AI Furnas Dataset.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2022 > PTL-AI Furnas Dataset: A Public Dataset for Fault Detection in Power Transmission Lines Using Aerial Images
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPEW34M/47LTDJ5
zipped data URLhttp://urlib.net/zip/8JMKD3MGPEW34M/47LTDJ5
Languageen
Target Fileoliveira-33_inpe.pdf
User Groupfred_s0@yahoo.com.br
Visibilityshown
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/495MHJ8
Citing Item Listsid.inpe.br/sibgrapi/2023/05.19.12.10 6
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage edition editor electronicmailaddress group holdercode isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project publisher publisheraddress readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session sponsor subject tertiarymark type url versiontype volume


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