Identity statement area
Reference TypeConference Paper (Conference Proceedings)
Last Update2005: (UTC) administrator
Metadata Last Update2020: (UTC) administrator
Citation KeyNeryCaPáQuMaCa:2005:DeApFe
TitleDetermining the appropriate feature set for fish classification tasks
Access Date2021, Nov. 27
Number of Files1
Size255 KiB
Context area
Author1 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
Affiliation1 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
EditorRodrigues, Maria Andréia Formico
Frery, Alejandro César
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 18 (SIBGRAPI)
Conference LocationNatal
Date9-12 Oct. 2005
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)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 Stagecompleted
Content TypeExternal Contribution
Keywordsobject classification
feature extraction
feature selection
fish classification
AbstractWe 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.
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Target Filepaduaf_fishclassification.pdf
User Groupcardeal
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