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dc.contributor.author |
BENAYED, Sarah |
|
dc.date.accessioned |
2022-06-20T07:55:15Z |
|
dc.date.available |
2022-06-20T07:55:15Z |
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dc.date.issued |
2021-06-27 |
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dc.identifier.uri |
http://e-biblio.univ-mosta.dz/handle/123456789/20794 |
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dc.description.abstract |
bstract : Facial detection involves developing code that, in an arbi-
trary image, can detect and locate human faces. It is gaining interest as an
important research area with important applications in security surveillance,
human-machine interaction, and other areas of computer vision and machine
learning. Many methods have been developed with several approaches. The
majority of the approaches used are based on two tasks. The rst is the
feature extraction task, it concerns the precise digital description of what
distinguishes human faces from other objects. The second task is usually a
supervised classi cation algorithm which will have to recognize a face from
a non-face with good precision.
The objective of our work is to use an interior point method, in order to
solve the quadratic program in SVMs. We will then focus on the behavior of
th |
en_US |
dc.language.iso |
fr |
en_US |
dc.relation.ispartofseries |
MMAT303; |
|
dc.title |
les méthodes de point intèieur pour la dètection faciale |
en_US |
dc.type |
Other |
en_US |
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