Reference TypeConference Proceedings
Citation KeyNeryCaPáQuMaCa:2005:DeApFe
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
TitleDetermining the appropriate feature set for fish classification tasks
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 18 (SIBGRAPI)
EditorRodrigues, Maria Andréia Formico
Frery, Alejandro César
Book TitleProceedings
Date9-12 Oct. 2005
Publisher CityLos Alamitos
PublisherIEEE Computer Society
Conference LocationNatal
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.
Tertiary TypeFull Paper
Size255 KiB
Number of Files1
Target Filepaduaf_fishclassification.pdf
Last Update2005: administrator
Metadata Last Update2020: administrator {D 2005}
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History2008-07-17 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
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Access Date2020, Nov. 27