dc.contributor.author |
BOUSAHBA, Nassima |
|
dc.contributor.author |
ADJOUDJ, Reda |
|
dc.contributor.author |
BELHIA, Souaad |
|
dc.contributor.author |
CHACHOU, Lamia |
|
dc.date.accessioned |
2022-08-06T21:52:25Z |
|
dc.date.available |
2022-08-06T21:52:25Z |
|
dc.date.issued |
2022-08-06 |
|
dc.identifier.issn |
2210-142X |
|
dc.identifier.uri |
https://journal.uob.edu.bh:443/handle/123456789/4641 |
|
dc.description.abstract |
In biometric systems, reducing the data dimensionality without compromising intrinsic information is essential in pre-processing high-dimensional data. Many states of the art use techniques to minimize the dimensionality of such data and avoid the so-called curse of dimensionality. When operating on limited datasets, supervised methods suffer from over fitting. Reducing the semi-supervised dimensionality in the next comparison or classification module can affect the recognition efficiency. This article introduces a novel multi- view multimodal semi-supervised dimensionality reduction methodology that applies Multi-view Multidimensional scaling dimensionality reduction based on Gabor 2D-Log extraction features and Fuzzy Multiclass SVM classification (FMSVM), respectively. In addition, it examines its application to multi-view multimodal biometric processing, especially multi-view faces, and fingerprints. An experimental study was conducted, and the results emphasize that this methodology surpasses baseline supervised and semi-supervised methods. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
University Of Bahrain |
en_US |
dc.subject |
Dimensionality reduction |
en_US |
dc.subject |
person identification |
en_US |
dc.subject |
multi-view multimodal learning |
en_US |
dc.subject |
MV-MDS |
en_US |
dc.subject |
FMSVM |
en_US |
dc.title |
Dimensionality Reduction Method Apply for Multi-view Multimodal Person Identification |
en_US |
dc.identifier.doi |
https://dx.doi.org/10.12785/ijcds/120155 |
|
dc.volume |
12 |
en_US |
dc.issue |
1 |
en_US |
dc.pagestart |
675 |
en_US |
dc.pageend |
685 |
en_US |
dc.contributor.authorcountry |
Algeria |
en_US |
dc.contributor.authorcountry |
Canada |
en_US |
dc.contributor.authoraffiliation |
EEDIS Laboratory, Djillali Liabes University, Sidi Bel Abbes, Algeria 2Hassiba Benbouali University, Chlef |
en_US |
dc.contributor.authoraffiliation |
College Superieur de Montreal (C.S.M), Quebec |
en_US |
dc.source.title |
International Journal of Computing and Digital Systems |
en_US |
dc.abbreviatedsourcetitle |
IJCDS |
en_US |