1. Identity statement | |
Reference Type | Conference Paper (Conference Proceedings) |
Site | sibgrapi.sid.inpe.br |
Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH |
Identifier | 8JMKD3MGPAW/3M3C9G8 |
Repository | sid.inpe.br/sibgrapi/2016/07.08.22.58 |
Last Update | 2016:07.08.22.58.58 (UTC) administrator |
Metadata Repository | sid.inpe.br/sibgrapi/2016/07.08.22.58.58 |
Metadata Last Update | 2022:06.14.00.08.18 (UTC) administrator |
DOI | 10.1109/SIBGRAPI.2016.062 |
Citation Key | AfonsoVidKurFalPap:2016:LeClSe |
Title | Learning to Classify Seismic Images with Deep Optimum-Path Forest |
Format | On-line |
Year | 2016 |
Access Date | 2024, May 03 |
Number of Files | 1 |
Size | 754 KiB |
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2. Context | |
Author | 1 Afonso, Luis Claudio Sugi 2 Vidal, Alexandre Campane 3 Kuroda, Michelle Chaves 4 Falcao, Alexandre Xavier 5 Papa, Joao Paulo |
Affiliation | 1 Federal University of Sao Carlos 2 University of Campinas 3 University of Campinas 4 University of Campinas 5 Sao Paulo State University |
Editor | Aliaga, Daniel G. Davis, Larry S. Farias, Ricardo C. Fernandes, Leandro A. F. Gibson, Stuart J. Giraldi, Gilson A. Gois, João Paulo Maciel, Anderson Menotti, David Miranda, Paulo A. V. Musse, Soraia Namikawa, Laercio Pamplona, Mauricio Papa, João Paulo Santos, Jefersson dos Schwartz, William Robson Thomaz, Carlos E. |
e-Mail Address | papa.joaopaulo@gmail.com |
Conference Name | Conference on Graphics, Patterns and Images, 29 (SIBGRAPI) |
Conference Location | São José dos Campos, SP, Brazil |
Date | 4-7 Oct. 2016 |
Publisher | IEEE Computer Society´s Conference Publishing Services |
Publisher City | Los Alamitos |
Book Title | Proceedings |
Tertiary Type | Full Paper |
History (UTC) | 2016-07-08 22:58:58 :: papa.joaopaulo@gmail.com -> administrator :: 2016-10-05 14:49:09 :: administrator -> papa.joaopaulo@gmail.com :: 2016 2016-10-13 17:38:03 :: papa.joaopaulo@gmail.com -> administrator :: 2016 2022-06-14 00:08:18 :: administrator -> :: 2016 |
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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 | Optimum-Path Forest Image Clustering Deep Representations Seismic Images |
Abstract | Due to the lack of labeled information, clustering techniques have been paramount in the last years once more. In this paper, inspired by the deep learning phenomenon, we presented a multi-scale approach to obtain more refined cluster representations of the Optimum-Path Forest (OPF) classifier, which has obtained promising results in a number of works in the literature. Here, we propose to fill a gap in OPF-based works by using a deep-driven representation of the feature space. Additionally, we validated the work in the context of high resolution seismic images aiming at petroleum exploration, as well as in general-purpose applications. Quantitative and qualitative analysis are conducted in order to assess the robustness of the proposed approach. |
Arrangement 1 | urlib.net > SDLA > Fonds > SIBGRAPI 2016 > Learning to Classify... |
Arrangement 2 | urlib.net > SDLA > Fonds > Full Index > Learning to Classify... |
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/3M3C9G8 |
zipped data URL | http://urlib.net/zip/8JMKD3MGPAW/3M3C9G8 |
Language | en |
Target File | paper.pdf |
User Group | papa.joaopaulo@gmail.com |
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/3M2D4LP 8JMKD3MGPEW34M/4742MCS |
Citing Item List | sid.inpe.br/sibgrapi/2016/07.02.23.50 9 sid.inpe.br/sibgrapi/2022/06.10.21.49 1 |
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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