| 1. Identity statement | ||||
| Reference Type | Conference Paper (Conference Proceedings) | |||
| Site | sibgrapi.sid.inpe.br | |||
| Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH | |||
| Identifier | 8JMKD3MGPAW/3PFRT45 | |||
| Repository | sid.inpe.br/sibgrapi/2017/08.22.00.41 | |||
| Last Update | 2017:08.22.13.58.53 (UTC) administrator | |||
| Metadata Repository | sid.inpe.br/sibgrapi/2017/08.22.00.41.47 | |||
| Metadata Last Update | 2022:06.14.00.09.01 (UTC) administrator | |||
| DOI | 10.1109/SIBGRAPI.2017.57 | |||
| Citation Key | CastroFeiRosDiaSan:2017:CoAnDe | |||
| Title | A Comparative Analysis of Deep Learning Techniques for Sub-tropical Crop Types Recognition from Multitemporal Optical/SAR Image Sequences  | |||
| Format | On-line | |||
| Year | 2017 | |||
| Access Date | 2024, Apr. 30 | |||
| Number of Files | 1 | |||
| Size | 22342 KiB | |||
| 2. Context | ||||
| Author | 1 Castro, Jose Bermudez 2 Feitosa, Raul Queiroz 3 Rosa, Laura Cue La 4 Diaz, Pedro Achanccaray 5 Sanches, Ieda | |||
| Group | 1 2 3 4 5 DIDSR-CGOBT-INPE-MCTIC-GOV-BR | |||
| Affiliation | 1 Pontifical Catholic University of Rio de Janeiro 2 Pontifical Catholic University of Rio de Janeiro 3 Pontifical Catholic University of Rio de Janeiro 4 Pontifical Catholic University of Rio de Janeiro 5 National Institute for Space Research | |||
| 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 | bermudez@ele.puc-rio.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) | 2017-08-22 13:58:53 :: bermudez@ele.puc-rio.br -> administrator :: 2017 2022-06-14 00:09:01 :: administrator -> :: 2017 | |||
| 3. Content and structure | ||||
| Is the master or a copy? | is the master | |||
| Content Stage | completed | |||
| Transferable | 1 | |||
| Version Type | finaldraft | |||
| Keywords | Crop Recognition Multitemporal Images Autoencoders Convolutional Neural Networks | |||
| Abstract | Remote Sensing (RS) data have been increasingly applied to assess agricultural yield, production and crop condition. In tropical areas, crop dynamics are complex due to multiple agricultural practices such as irrigation, non-tillage, crop rotation and multiple harvest per year. Spatial and temporal information can improve the performance in land-cover and crop type classification tasks. In this context Deep Learning (DL) have emerged as a powerful state-of-the-art technique in the RS community. This work presents a comparative analysis of traditional and DL (supervised and unsupervised) approaches for crop classification on sequences of multitemporal optical and SAR images. Three different approaches are compared: the image stacking approach, which is used as baseline, and two DL based approaches using Autoencoders (AEs) and Convolutional Neural Networks (CNNs). Experiments were carried out in two datasets from two different municipalities in Brazil, Ipu\~{a} in S\~{a}o Paulo state and Campo Verde in Mato Grosso state. It is shown that CNN and AE outperformed the traditional approach based on image stacking in terms of Overall Accuracy and Class Accuracy. | |||
| Arrangement 1 | urlib.net > SDLA > Fonds > SIBGRAPI 2017 > A Comparative Analysis... | |||
| Arrangement 2 | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > A Comparative Analysis... | |||
| Arrangement 3 | urlib.net > SDLA > Fonds > Full Index > A Comparative Analysis... | |||
| doc Directory Content | access | |||
| source Directory Content |
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| agreement Directory Content |
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| 4. Conditions of access and use | ||||
| data URL | http://urlib.net/ibi/8JMKD3MGPAW/3PFRT45 | |||
| zipped data URL | http://urlib.net/zip/8JMKD3MGPAW/3PFRT45 | |||
| Language | en | |||
| Target File | 2017_SIBGRAPI_BERMUDEZ.pdf | |||
| User Group | bermudez@ele.puc-rio.br | |||
| Visibility | shown | |||
| Read Permission | allow from all | |||
| Update Permission | not transferred | |||
| 5. Allied materials | ||||
| Mirror Repository | sid.inpe.br/banon/2001/03.30.15.38.24 | |||
| Next Higher Units | 8JMKD3MGPAW/3PKCC58 8JMKD3MGPCW/3ER446E 8JMKD3MGPEW34M/4742MCS | |||
| Citing Item List | sid.inpe.br/sibgrapi/2017/09.12.13.04 5 sid.inpe.br/sibgrapi/2022/06.10.21.49 1 | |||
| Host Collection | sid.inpe.br/banon/2001/03.30.15.38 | |||
| 6. Notes | ||||
| Empty Fields | archivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination edition electronicmailaddress isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url volume | |||