A Novel Fuzzy Visual Object Classification Approach
| dc.contributor.author | Altintakan, Umit Lutfu | |
| dc.contributor.author | Yazici, Adnan | |
| dc.contributor.author | Koyuncu, Murat | |
| dc.contributor.other | Information Systems Engineering | |
| dc.contributor.other | 06. School Of Engineering | |
| dc.contributor.other | 01. Atılım University | |
| dc.date.accessioned | 2024-10-06T10:57:06Z | |
| dc.date.available | 2024-10-06T10:57:06Z | |
| dc.date.issued | 2012 | |
| dc.description.abstract | Support Vector Machines (SVMs) have been extensively used for visual object classification to bridge the semantic gap between the low level features and high level concepts. SVM treats each training input equally during the construction of its decision surface which results in poor learning machines if training data include outliers. In this paper, a novel fuzzy visual object classification approach utilizing Self-Organizing Maps (SOMs) in SVM is proposed. The experimental results show the effectiveness of the proposed Fuzzy SVM compared to the traditional SVM. | en_US |
| dc.description.sponsorship | Scientific and Technological Research Council of Turkey (TUBITAK) [EEEAG 109E014] | en_US |
| dc.description.sponsorship | This work is supported in part by Scientific and Technological Research Council of Turkey (TUBITAK) with the research Grant no. EEEAG 109E014. | en_US |
| dc.identifier.isbn | 9781467315067 | |
| dc.identifier.issn | 1098-7584 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14411/8672 | |
| dc.language.iso | en | en_US |
| dc.publisher | Ieee | en_US |
| dc.relation.ispartof | IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) -- JUN 10-15, 2012 -- Brisbane, AUSTRALIA | en_US |
| dc.relation.ispartofseries | IEEE International Conference on Fuzzy Systems | |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | fuzzy suppor vector machines | en_US |
| dc.subject | membership function | en_US |
| dc.subject | image classification | en_US |
| dc.subject | self-organizing maps | en_US |
| dc.title | A Novel Fuzzy Visual Object Classification Approach | en_US |
| dc.type | Conference Object | en_US |
| dspace.entity.type | Publication | |
| gdc.author.institutional | Koyuncu, Murat | |
| gdc.author.wosid | Koyuncu, Murat/C-9407-2017 | |
| gdc.coar.access | metadata only access | |
| gdc.coar.type | text::conference output | |
| gdc.description.department | Atılım University | en_US |
| gdc.description.departmenttemp | [Altintakan, Umit Lutfu; Yazici, Adnan] Middle E Tech Univ, Dept Comp Engn, TR-06531 Ankara, Turkey; [Koyuncu, Murat] Atilim Univ, Dept Comp Engn, Ankara, Turkey | en_US |
| gdc.description.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
| gdc.description.scopusquality | Q3 | |
| gdc.description.woscitationindex | Conference Proceedings Citation Index - Science | |
| gdc.identifier.wos | WOS:000309188200124 | |
| gdc.wos.citedcount | 0 | |
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