1. Identity statement | |
Reference Type | Conference Paper (Conference Proceedings) |
Site | sibgrapi.sid.inpe.br |
Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH |
Identifier | 6qtX3pFwXQZeBBx/vRThU |
Repository | sid.inpe.br/banon/2002/10.24.10.41 |
Last Update | 2002:09.03.03.00.00 (UTC) administrator |
Metadata Repository | sid.inpe.br/banon/2002/10.24.10.41.18 |
Metadata Last Update | 2022:06.14.00.11.51 (UTC) administrator |
DOI | 10.1109/SIBGRA.2002.1167129 |
Citation Key | MartinsGuimFons:2002:TeFeNe |
Title | Texture feature neural classifier for remote sensing image retrieval systems |
Year | 2002 |
Access Date | 2024, May 09 |
Number of Files | 1 |
Size | 863 KiB |
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2. Context | |
Author | 1 Martins, Mauricio Pozzobon 2 Guimaraes, Lamartine N. Frutuoso 3 Fonseca, Leila Maria Garcia |
Editor | Gonçalves, Luiz Marcos Garcia Musse, Soraia Raupp Comba, João Luiz Dihl Giraldi, Gilson Dreux, Marcelo |
Conference Name | Brazilian Symposium on Computer Graphics and Image Processing, 15 (SIBGRAPI) |
Conference Location | Fortaleza, CE, Brazil |
Date | 10-10 Oct. 2002 |
Publisher | IEEE Computer Society |
Publisher City | Los Alamitos |
Book Title | Proceedings |
Tertiary Type | Full Paper |
Organization | SBC - Brazilian Computer Society |
History (UTC) | 2008-07-17 14:10:47 :: administrator -> banon :: 2008-08-26 15:21:22 :: banon -> administrator :: 2009-08-13 20:36:41 :: administrator -> banon :: 2010-08-28 20:00:07 :: banon -> administrator :: 2022-06-14 00:11:51 :: administrator -> :: 2002 |
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3. Content and structure | |
Is the master or a copy? | is the master |
Content Stage | completed |
Transferable | 1 |
Version Type | finaldraft |
Abstract | Texture information is useful for image data browsing and retrieval. The goal of this paper is to present a texture classification system for remote sensing images addressed to the administration of great collections of those images. The proposed classifier is a hybrid system composed by an unsupervised neural network and a supervised one. Starting from a small portion of the image (pattern) the system should recognize the most similar class to the pattern in a database as well as to identify the images that contain similar patterns. The texture feature vectors used to characterize the patterns are obtained from the images processed by a bank of Gabor Filters. Some experimental results using textures of the Brodatz album, multi-spectral and radar images have presented here. |
Arrangement 1 | urlib.net > SDLA > Fonds > SIBGRAPI 2002 > Texture feature neural... |
Arrangement 2 | urlib.net > SDLA > Fonds > Full Index > Texture feature neural... |
doc Directory Content | access |
source Directory Content | there are no files |
agreement Directory Content | there are no files |
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4. Conditions of access and use | |
data URL | http://urlib.net/ibi/6qtX3pFwXQZeBBx/vRThU |
zipped data URL | http://urlib.net/zip/6qtX3pFwXQZeBBx/vRThU |
Language | en |
Target File | 81.pdf |
User Group | administrator |
Visibility | shown |
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5. Allied materials | |
Next Higher Units | 8JMKD3MGPEW34M/46QCSHP 8JMKD3MGPEW34M/4742MCS |
Citing Item List | sid.inpe.br/sibgrapi/2022/05.01.04.11 5 |
Host Collection | sid.inpe.br/banon/2001/03.30.15.38 |
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6. Notes | |
Notes | The conference was held in Fortaleza, CE, Brazil, from October 7 to 10. |
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