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Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Identifier8JMKD3MGPAW/3PEUQJS
Repositorysid.inpe.br/sibgrapi/2017/08.16.12.58
Last Update2017:08.16.12.58.57 administrator
Metadatasid.inpe.br/sibgrapi/2017/08.16.12.58.57
Metadata Last Update2020:02.19.02.01.18 administrator
Citation KeyMedeirosNetoBragHarbJúni:2017:DrMeGe
TitleDrosophila melanogaster Gender Classification Based on Fractal Dimension
FormatOn-line
Year2017
DateOct. 17-20, 2017
Access Date2021, Jan. 19
Number of Files1
Size1350 KiB
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Author1 Medeiros Neto, Francisco Gerardo
2 Braga, Ítalo Rodrigues
3 Harber, Matthew Henry
4 Júnior, Iális Cavalcante de Paula
Affiliation1 Federal University of Ceará
2 Federal University of Ceará
3 GeoPoll
4 Federal University of Ceará
EditorTorchelsen, Rafael Piccin
Nascimento, Erickson Rangel do
Panozzo, Daniele
Liu, Zicheng
Farias, Mylčne
Viera, Thales
Sacht, Leonardo
Ferreira, Nivan
Comba, Joăo Luiz Dihl
Hirata, Nina
Schiavon Porto, Marcelo
Vital, Creto
Pagot, Christian Azambuja
Petronetto, Fabiano
Clua, Esteban
Cardeal, Flávio
e-Mail Addressfcogmneto@gmail.com
Conference NameConference on Graphics, Patterns and Images, 30 (SIBGRAPI)
Conference LocationNiterói, RJ
Book TitleProceedings
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Tertiary TypeFull Paper
History2017-08-16 12:58:57 :: fcogmneto@gmail.com -> administrator ::
2020-02-19 02:01:18 :: administrator -> :: 2017
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Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Keywordsstationary wavelet transform, Canny filter, fractal dimension, classification.
AbstractBiometrics, previously used only in human identification, can help experts in the analysis of biological images. Flies of the genus Drosophila have become model organisms by almost global presence and short life cycle. Facial recognition techniques and geometric morphometry can be used in image processing for classification. The latter requires human interaction. This work details a methodology based on stationary wavelet transform, Canny filter and fractal dimension aimed to infer the gender of Drosophila melanogaster based on images of their wings. The combination of variation in the training and test samples and classification methods showed the proposed algorithms accuracy rate, 90%, outperformed other methods. The proposed methodology proved efficient by using a reduced number of attributes and did not require human interaction for feature extraction (landmarks).
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data URLhttp://urlib.net/rep/8JMKD3MGPAW/3PEUQJS
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3PEUQJS
Languageen
Target Filesibgrapi-2017-cr.pdf
User Groupfcogmneto@gmail.com
Visibilityshown
Update Permissionnot transferred
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Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPAW/3PJT9LS
8JMKD3MGPAW/3PKCC58
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
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