Identity statement area | |
Reference Type | Conference Paper (Conference Proceedings) |
Site | sibgrapi.sid.inpe.br |
Identifier | 6qtX3pFwXQZeBBx/GJPfJ |
Repository | sid.inpe.br/banon/2005/07.12.19.51 |
Last Update | 2005:07.13.03.00.00 administrator |
Metadata | sid.inpe.br/banon/2005/07.12.19.51.36 |
Metadata Last Update | 2020:02.19.03.19.13 administrator |
Citation Key | NeryCaPáQuMaCa:2005:DeApFe |
Title | Determining the appropriate feature set for fish classification tasks  |
Format | On-line |
Year | 2005 |
Date | 9-12 Oct. 2005 |
Access Date | 2021, Jan. 19 |
Number of Files | 1 |
Size | 255 KiB |
Context area | |
Author | 1 Nery, Marcelo Souza 2 Campos, Mario Fernando Montenegro 3 Pádua, Flávio Luis Cardeal 4 Queiroz Neto, José Pinheiro de 5 Machado, Alexei Manso Correa 6 Carceroni, Rodrigo Lima |
Affiliation | 1 Departamento de Ciência da Computação - Universidade Federal de Minas Gerais 2 Pontifícia Universidade Católica de Minas Gerais 3 Centro Federal de Educação Tecnológica do Amazonas |
Editor | Rodrigues, Maria Andréia Formico Frery, Alejandro César |
e-Mail Address | cardeal@dcc.ufmg.br |
Conference Name | Brazilian Symposium on Computer Graphics and Image Processing, 18 (SIBGRAPI) |
Conference Location | Natal |
Book Title | Proceedings |
Publisher | IEEE Computer Society |
Publisher City | Los Alamitos |
Tertiary Type | Full Paper |
History | 2008-07-17 14:11:00 :: cardeal -> banon :: 2008-08-26 15:17:02 :: banon -> administrator :: 2009-08-13 20:37:48 :: administrator -> banon :: 2010-08-28 20:01:18 :: banon -> administrator :: 2020-02-19 03:19:13 :: administrator -> :: 2005 |
Content and structure area | |
Is the master or a copy? | is the master |
Content Stage | completed |
Transferable | 1 |
Content Type | External Contribution |
Keywords | object classification, feature extraction, feature selection, fish classification. |
Abstract | We present a novel fish classification methodology based on a robust feature selection technique. Unlike existing works for fish classification, which propose descriptors and do not analyze their individual impacts in the whole classification task, we propose a general set of features and their correspondent weights that should be used as a priori information by the classifier. In this sense, instead of studying techniques for improving the classifiers structure itself, we consider it as a "black box" and focus our research in the determination of which input information must bring a robust fish discrimination. All the experiments were performed with fish species of Rio Grande river in Minas Gerais, Brazil. This work has been developed as part of a wider research, which has as main goal the development of effective fish ladders for the Brazilian dams. |
source Directory Content | there are no files |
agreement Directory Content | there are no files |
Conditions of access and use area | |
data URL | http://urlib.net/rep/6qtX3pFwXQZeBBx/GJPfJ |
zipped data URL | http://urlib.net/zip/6qtX3pFwXQZeBBx/GJPfJ |
Language | en |
Target File | paduaf_fishclassification.pdf |
User Group | cardeal administrator |
Visibility | shown |
Allied materials area | |
Host Collection | sid.inpe.br/banon/2001/03.30.15.38 |
Notes area | |
Empty Fields | accessionnumber archivingpolicy archivist area callnumber copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi edition electronicmailaddress group holdercode isbn issn label lineage mark mirrorrepository nextedition nexthigherunit notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume |
| |