Close

1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier6qtX3pFwXQZeBBx/GLv3s
Repositorysid.inpe.br/banon/2005/07.15.16.20
Last Update2005:07.15.03.00.00 (UTC) administrator
Metadata Repositorysid.inpe.br/banon/2005/07.15.16.20.19
Metadata Last Update2022:06.14.00.13.03 (UTC) administrator
DOI10.1109/SIBGRAPI.2005.16
Citation KeyHirata:2005:BiImOp
TitleBinary image operator design based on stacked generalization
FormatOn-line
Year2005
Access Date2024, Apr. 29
Number of Files1
Size506 KiB
2. Context
AuthorHirata, Nina Sumiko Tomita
AffiliationDepartment of Computer Science, Institute of Mathematics and Statistics, University of Sao Paulo
EditorRodrigues, Maria Andr?ia Formico
Frery, Alejandro C?sar
e-Mail Addressnina@ime.usp.br
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 18 (SIBGRAPI)
Conference LocationNatal, RN, Brazil
Date9-12 Oct. 2005
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2008-07-17 14:11:00 :: nina -> banon ::
2008-08-26 15:17:02 :: banon -> administrator ::
2009-08-13 20:37:53 :: administrator -> banon ::
2010-08-28 20:01:19 :: banon -> administrator ::
2022-06-14 00:13:03 :: administrator -> :: 2005
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywordsstacked generalization
image operator design
multi-stage training
AbstractStacked generalization refers to any learning schema that consists of multiple levels of training. Level zero classifiers are those that depend solely on input data while classifiers at other levels may use the output of lower levels as the input. Stacked generalization can be used to address the difficulties related to the design of image operators defined on large windows. This paper describes a simple stacked generalization schema for the design of binary image operators and presents several application examples that show its effectiveness as a training schema.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2005 > Binary image operator...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Binary image operator...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Contentthere are no files
4. Conditions of access and use
data URLhttp://urlib.net/ibi/6qtX3pFwXQZeBBx/GLv3s
zipped data URLhttp://urlib.net/zip/6qtX3pFwXQZeBBx/GLv3s
Languageen
Target Filehiratan.pdf
User Groupnina
administrator
Visibilityshown
5. Allied materials
Next Higher Units8JMKD3MGPEW34M/46R3ED5
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2022/05.05.04.08 7
sid.inpe.br/banon/2001/03.30.15.38.24 1
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage edition electronicmailaddress group isbn issn label lineage mark mirrorrepository nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url volume


Close