1. Identity statement | |
Reference Type | Conference Paper (Conference Proceedings) |
Site | sibgrapi.sid.inpe.br |
Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH |
Identifier | 8JMKD3MGPEW34M/45E3ET5 |
Repository | sid.inpe.br/sibgrapi/2021/09.13.10.35 |
Last Update | 2021:09.13.10.35.02 (UTC) administrator |
Metadata Repository | sid.inpe.br/sibgrapi/2021/09.13.10.35.02 |
Metadata Last Update | 2022:09.10.00.16.17 (UTC) administrator |
Citation Key | SganderlaMaurSantPere:2021:DeClOb |
Title | Detecção e Classificação de Objetos Presentes em Imagens Aéreas de Drones de Ambientes Urbanos |
Format | On-line |
Year | 2021 |
Access Date | 2024, May 06 |
Number of Files | 1 |
Size | 1130 KiB |
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2. Context | |
Author | 1 Sganderla, Guilherme Rodrigues 2 Mauricio, Claudio Roberto Marquetto 3 Santos, Valéria Nunes dos 4 Peres, Fabiana Frata Frata |
Affiliation | 1 Universidade Estadual do Oeste do Paraná 2 Universidade Estadual do Oeste do Paraná 3 Fundação Parque Tecnológico Itaipu 4 Universidade Estadual do Oeste do Paraná |
Editor | Paiva, 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 Address | grodriguessganderla@gmail.com |
Conference Name | Conference on Graphics, Patterns and Images, 34 (SIBGRAPI) |
Conference Location | Gramado, RS, Brazil (virtual) |
Date | 18-22 Oct. 2021 |
Publisher | Sociedade Brasileira de Computação |
Publisher City | Porto Alegre |
Book Title | Proceedings |
Tertiary Type | Undergraduate Work |
History (UTC) | 2021-09-13 10:35:02 :: grodriguessganderla@gmail.com -> administrator :: 2022-09-10 00:16:17 :: administrator -> :: 2021 |
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3. Content and structure | |
Is the master or a copy? | is the master |
Content Stage | completed |
Transferable | 1 |
Keywords | Drone Detecção de Objetos YOLOv5 |
Abstract | Through large data sets, it is possible to train and instruct a machine with skills to perform tasks previously performed only by humans. This possibility has become increasingly real with the use of Deep Learning and powerful algorithms that have been developed over time. Among them is YOLO, a Convolutional Neural Network algorithm that allows several uses, including the detection and classification of objects contained in images of urban environments, such as people and vehicles, allowing the identification and location of objects within the images. This work presents a model for detecting and classifying common object classes in urban environments - People, Small Vehicles, Medium-Vehicles and Large-Vehicles). For this project we used a combination of 3 datasets of aerial drone images of urban environments (Stanford Drone Dataset, Vision Meets Drone, The Unmanned Aerial Vehicle Benchmark Object Detection and Tracking). The result obtained from the initial training of this YOLO algorithm was an average accuracy of 67.2%. |
Arrangement | urlib.net > SDLA > Fonds > SIBGRAPI 2021 > Detecção e Classificação... |
doc Directory Content | access |
source Directory Content | there are no files |
agreement Directory Content | |
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4. Conditions of access and use | |
data URL | http://urlib.net/ibi/8JMKD3MGPEW34M/45E3ET5 |
zipped data URL | http://urlib.net/zip/8JMKD3MGPEW34M/45E3ET5 |
Language | pt |
Target File | SIBGRAPI_2021_GUILHERME(1).pdf |
User Group | grodriguessganderla@gmail.com |
Visibility | shown |
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5. Allied materials | |
Mirror Repository | sid.inpe.br/banon/2001/03.30.15.38.24 |
Next Higher Units | 8JMKD3MGPEW34M/45PQ3RS |
Citing Item List | sid.inpe.br/sibgrapi/2021/11.12.11.46 4 |
Host Collection | sid.inpe.br/banon/2001/03.30.15.38 |
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6. Notes | |
Empty Fields | archivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi 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 versiontype volume |
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