Identity statement area | |
Reference Type | Conference Paper (Conference Proceedings) |
Site | sibgrapi.sid.inpe.br |
Identifier | 8JMKD3MGPAW/3PEUQJS |
Repository | sid.inpe.br/sibgrapi/2017/08.16.12.58 |
Last Update | 2017:08.16.12.58.57 administrator |
Metadata | sid.inpe.br/sibgrapi/2017/08.16.12.58.57 |
Metadata Last Update | 2020:02.19.02.01.18 administrator |
Citation Key | MedeirosNetoBragHarbJúni:2017:DrMeGe |
Title | Drosophila melanogaster Gender Classification Based on Fractal Dimension  |
Format | On-line |
Year | 2017 |
Date | Oct. 17-20, 2017 |
Access Date | 2021, Jan. 19 |
Number of Files | 1 |
Size | 1350 KiB |
Context area | |
Author | 1 Medeiros Neto, Francisco Gerardo 2 Braga, Ítalo Rodrigues 3 Harber, Matthew Henry 4 Júnior, Iális Cavalcante de Paula |
Affiliation | 1 Federal University of Ceará 2 Federal University of Ceará 3 GeoPoll 4 Federal University of Ceará |
Editor | Torchelsen, 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 Address | fcogmneto@gmail.com |
Conference Name | Conference on Graphics, Patterns and Images, 30 (SIBGRAPI) |
Conference Location | Niterói, RJ |
Book Title | Proceedings |
Publisher | IEEE Computer Society |
Publisher City | Los Alamitos |
Tertiary Type | Full Paper |
History | 2017-08-16 12:58:57 :: fcogmneto@gmail.com -> administrator :: 2020-02-19 02:01:18 :: administrator -> :: 2017 |
Content and structure area | |
Is the master or a copy? | is the master |
Content Stage | completed |
Transferable | 1 |
Content Type | External Contribution |
Keywords | stationary wavelet transform, Canny filter, fractal dimension, classification. |
Abstract | Biometrics, 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). |
source Directory Content | there are no files |
agreement Directory Content | |
Conditions of access and use area | |
data URL | http://urlib.net/rep/8JMKD3MGPAW/3PEUQJS |
zipped data URL | http://urlib.net/zip/8JMKD3MGPAW/3PEUQJS |
Language | en |
Target File | sibgrapi-2017-cr.pdf |
User Group | fcogmneto@gmail.com |
Visibility | shown |
Update Permission | not transferred |
Allied materials area | |
Mirror Repository | sid.inpe.br/banon/2001/03.30.15.38.24 |
Next Higher Units | 8JMKD3MGPAW/3PJT9LS 8JMKD3MGPAW/3PKCC58 |
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 doi edition electronicmailaddress group holdercode isbn issn label lineage mark nextedition 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 |
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