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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPEW34M/45C7QNL
Repositorysid.inpe.br/sibgrapi/2021/09.02.03.12
Last Update2021:09.02.03.12.10 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2021/09.02.03.12.10
Metadata Last Update2022:06.14.00.00.19 (UTC) administrator
DOI10.1109/SIBGRAPI54419.2021.00037
Citation KeyVieiraeSilvaFCSTSSSL:2021:DaMuPo
TitleSTN PLAD: A Dataset for Multi-Size Power Line Assets Detection in High-Resolution UAV Images
FormatOn-line
Year2021
Access Date2024, Apr. 26
Number of Files1
Size5519 KiB
2. Context
Author1 Vieira e Silva, André Luiz Buarque
2 Felix, Heitor de Castro
3 Chaves, Thiago de Menezes
4 Simões, Francisco Paulo Magalhães
5 Teichrieb, Veronica
6 dos Santos, Michel Mozinho
7 Santiago, Hemir da Cunha
8 Sgotti, Virginia Adélia Cordeiro
9 Lott Neto, Henrique Baptista Duffles Teixeira
Affiliation1 Voxar Labs, Centro de Informática, Universidade Federal de Pernambuco, Brazil  
2 Voxar Labs, Centro de Informática, Universidade Federal de Pernambuco, Brazil  
3 Voxar Labs, Centro de Informática, Universidade Federal de Pernambuco, Brazil  
4 Departamento de Computação, Universidade Federal Rural de Pernambuco, Brazil  
5 Voxar Labs, Centro de Informática, Universidade Federal de Pernambuco, Brazil  
6 In Forma Software, Brazil  
7 In Forma Software, Brazil  
8 In Forma Software, Brazil  
9 Sistema de Transmissão Nordeste, Brazil
EditorPaiva, Afonso
Menotti, David
Baranoski, Gladimir V. G.
Proença, Hugo Pedro
Junior, Antonio Lopes Apolinario
Papa, João Paulo
Pagliosa, Paulo
dos Santos, Thiago Oliveira
e Sá, Asla Medeiros
da Silveira, Thiago Lopes Trugillo
Brazil, Emilio Vital
Ponti, Moacir A.
Fernandes, Leandro A. F.
Avila, Sandra
e-Mail Addressalbvs@cin.ufpe.br
Conference NameConference on Graphics, Patterns and Images, 34 (SIBGRAPI)
Conference LocationGramado, RS, Brazil (virtual)
Date18-22 Oct. 2021
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2021-09-02 03:12:10 :: albvs@cin.ufpe.br -> administrator ::
2022-03-02 00:54:15 :: administrator -> menottid@gmail.com :: 2021
2022-03-02 13:40:28 :: menottid@gmail.com -> administrator :: 2021
2022-06-14 00:00:19 :: administrator -> :: 2021
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywordsobject detection
image dataset
inspection
power lines
deep learning
computer vision
uav
AbstractMany power line companies are using UAVs to perform their inspection processes instead of putting their workers at risk by making them climb high voltage power line towers, for instance. A crucial task for the inspection is to detect and classify assets in the power transmission lines. However, public data related to power line assets are scarce, preventing a faster evolution of this area. This work proposes the STN Power Line Assets Dataset, containing high-resolution and real-world images of multiple high-voltage power line components. It has 2,409 annotated objects divided into five classes: transmission tower, insulator, spacer, tower plate, and Stockbridge damper, which vary in size (resolution), orientation, illumination, angulation, and background. This work also presents an evaluation with popular deep object detection methods and MS-PAD, a new pipeline for detecting power line assets in hi-res UAV images. The latter outperforms the other methods achieving 89.2% mAP, showing considerable room for improvement. The STN PLAD dataset is publicly available at https://github.com/andreluizbvs/PLAD.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2021 > STN PLAD: A...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > STN PLAD: A...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPEW34M/45C7QNL
zipped data URLhttp://urlib.net/zip/8JMKD3MGPEW34M/45C7QNL
Languageen
Target File52.pdf
User Groupalbvs@cin.ufpe.br
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/45PQ3RS
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2021/11.12.11.46 3
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url volume


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