1. Identity statement | |
Reference Type | Conference Paper (Conference Proceedings) |
Site | sibgrapi.sid.inpe.br |
Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH |
Identifier | 8JMKD3MGPAW/3PFRKFL |
Repository | sid.inpe.br/sibgrapi/2017/08.21.23.09 |
Last Update | 2017:08.21.23.09.18 (UTC) administrator |
Metadata Repository | sid.inpe.br/sibgrapi/2017/08.21.23.09.18 |
Metadata Last Update | 2022:06.14.00.09.00 (UTC) administrator |
DOI | 10.1109/SIBGRAPI.2017.41 |
Citation Key | BaetaNoguMenoSant:2017:LeDeFe |
Title | Learning Deep Features on Multiple Scales for Coffee Crop Recognition |
Format | On-line |
Year | 2017 |
Access Date | 2024, Apr. 28 |
Number of Files | 1 |
Size | 8809 KiB |
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2. Context | |
Author | 1 Baeta, Rafael 2 Nogueira, Keiller 3 Menotti, David 4 Santos, Jefersson Alex dos |
Affiliation | 1 Universidade Federal de Minas Gerais 2 Universidade Federal de Minas Gerais 3 Universidade Federal do Paraná 4 Universidade Federal de Minas Gerais |
Editor | Torchelsen, Rafael Piccin Nascimento, Erickson Rangel do Panozzo, Daniele Liu, Zicheng Farias, Mylène Viera, Thales Sacht, Leonardo Ferreira, Nivan Comba, João Luiz Dihl Hirata, Nina Schiavon Porto, Marcelo Vital, Creto Pagot, Christian Azambuja Petronetto, Fabiano Clua, Esteban Cardeal, Flávio |
e-Mail Address | rbaeta@dcc.ufmg.br |
Conference Name | Conference on Graphics, Patterns and Images, 30 (SIBGRAPI) |
Conference Location | Niterói, RJ, Brazil |
Date | 17-20 Oct. 2017 |
Publisher | IEEE Computer Society |
Publisher City | Los Alamitos |
Book Title | Proceedings |
Tertiary Type | Full Paper |
History (UTC) | 2017-08-21 23:09:18 :: rbaeta@dcc.ufmg.br -> administrator :: 2022-06-14 00:09:00 :: administrator -> :: 2017 |
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3. Content and structure | |
Is the master or a copy? | is the master |
Content Stage | completed |
Transferable | 1 |
Version Type | finaldraft |
Keywords | Deep Learning Remote Sensing Coffee Crops High-resolution Images Agriculture |
Abstract | Geographic mapping of coffee crops by using remote sensing images and supervised classification has been a challenging research subject. Besides the intrinsic problems caused by the nature of multi-spectral information, coffee crops are non-seasonal and usually planted in mountains, which requires encoding and learning a huge diversity of patterns during the classifier training. In this paper, we propose a new approach for automatic mapping coffee crops by combining two recent trends on pattern recognition for remote sensing applications: deep learning and fusion/selection of features from multiple scales. The proposed approach is a pixel-wise strategy that consists in the training and combination of convolutional neural networks designed to receive as input different context windows around labeled pixels. Final maps are created by combining the output of those networks for a non-labeled set of pixels. Experimental results show that multiple scales produces better coffee crop maps than using single scales. Experiments also show the proposed approach is effective in comparison with baselines. |
Arrangement 1 | urlib.net > SDLA > Fonds > SIBGRAPI 2017 > Learning Deep Features... |
Arrangement 2 | urlib.net > SDLA > Fonds > Full Index > Learning Deep Features... |
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/8JMKD3MGPAW/3PFRKFL |
zipped data URL | http://urlib.net/zip/8JMKD3MGPAW/3PFRKFL |
Language | en |
Target File | PID4960341.pdf |
User Group | rbaeta@dcc.ufmg.br |
Visibility | shown |
Update Permission | not transferred |
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5. Allied materials | |
Mirror Repository | sid.inpe.br/banon/2001/03.30.15.38.24 |
Next Higher Units | 8JMKD3MGPAW/3PKCC58 8JMKD3MGPEW34M/4742MCS |
Citing Item List | sid.inpe.br/sibgrapi/2017/09.12.13.04 5 |
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 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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