1. Identity statement | |
Reference Type | Conference Paper (Conference Proceedings) |
Site | sibgrapi.sid.inpe.br |
Identifier | 8JMKD3MGPEW34M/47JU5QE |
Repository | sid.inpe.br/sibgrapi/2022/09.10.19.32 |
Last Update | 2022:09.10.19.32.31 (UTC) arbackes@yahoo.com.br |
Metadata Repository | sid.inpe.br/sibgrapi/2022/09.10.19.32.31 |
Metadata Last Update | 2023:05.23.04.20.42 (UTC) administrator |
DOI | 10.1109/SIBGRAPI55357.2022.9991781 |
Citation Key | SilvaJúnMarEscBac:2022:NoCoUA |
Title | Non-Linear co-registration in UAVs' images using deep learning |
Short Title | Non-Linear co-registration in UAVs' images using deep learning |
Format | On-line |
Year | 2022 |
Access Date | 2024, May 11 |
Number of Files | 1 |
Size | 3753 KiB |
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2. Context | |
Author | 1 Silva, Leandro Henrique Furtado Pinto 2 Júnior, Jocival Dantas Dias 3 Mari, João Fernando 4 Escarpinati, Mauricio Cunha 5 Backes, André Ricardo |
Affiliation | 1 School of Computer Science, Federal University of Uberlândia 2 School of Computer Science, Federal University of Uberlândia 3 Federal University of Viçosa, Campus Rio Paranaíba 4 School of Computer Science, Federal University of Uberlândia 5 School of Computer Science, Federal University of Uberlândia |
e-Mail Address | arbackes@yahoo.com.br |
Conference Name | Conference on Graphics, Patterns and Images, 35 (SIBGRAPI) |
Conference Location | Natal, RN |
Date | 24-27 Oct. 2022 |
Book Title | Proceedings |
Tertiary Type | Full Paper |
History (UTC) | 2022-09-10 19:32:31 :: arbackes@yahoo.com.br -> administrator :: 2023-05-23 04:20:42 :: administrator -> :: 2022 |
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3. Content and structure | |
Is the master or a copy? | is the master |
Content Stage | completed |
Transferable | 1 |
Keywords | image registration multispectral image deep learning precision agriculture UAV |
Abstract | Unmanned Aerial Vehicles (UAVs) has stood out for assisting, enhancing, and optimizing agricultural production. Images captured by UAVs allow a detailed view of the analyzed region since the flight occurs at low and medium altitudes (50m to 400m). In addition, there is a wide variety of sensors (RGB cameras, heat capture sensors, multi and hyperspectral cameras, among others), each with its own characteristics and capable of producing different information. In multi-spectral images acquisition, we use a distinct sensor to capture each image band and at different time, leading to misalignments. To tackle this problem we propose to train a deep neural network to predict the vector deformation fields to perform the registration between bands of a multi-spectral image. The proposed approach has an accuracy ranging from 89.90% to 93.79% in the task of estimating the displacement field between bands. With this field estimated by the network, it is possible to register between the bands without the need for manual marking of points. |
Arrangement | urlib.net > SDLA > Fonds > SIBGRAPI 2022 > Non-Linear co-registration in UAVs' images using deep learning |
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://sibgrapi.sid.inpe.br/ibi/8JMKD3MGPEW34M/47JU5QE |
zipped data URL | http://sibgrapi.sid.inpe.br/zip/8JMKD3MGPEW34M/47JU5QE |
Language | en |
Target File | backes_9.pdf |
User Group | arbackes@yahoo.com.br |
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/495MHJ8 |
Citing Item List | sid.inpe.br/sibgrapi/2023/05.19.12.10 6 sid.inpe.br/sibgrapi/2022/06.10.21.49 2 |
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 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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