Exploring Open Set Classification for Facial Recognition Applications

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dc.contributor.advisorKovács, Zita
dc.contributor.authorBatayneh, Hamzeh
dc.contributor.departmentDE--Informatikai Kar
dc.date.accessioned2022-11-14T11:29:07Z
dc.date.available2022-11-14T11:29:07Z
dc.date.created2022-11-10
dc.description.abstractIn this work we have proposed a system to perform open set classification for facial recognition applications and using incremental learning furthermore we have studied and explored all the different algorithms that enable us to perform that task. The algorithms included different computer vision and machine learning algorithms, where each played an important role in the final results. Different classifiers were tuned and tested using k fold cross validation techniques for different scenarios on the choke point dataset in order to find the classification algorithm that performs best for our task.
dc.description.correctorN.I.
dc.description.courseComputer Science Engineering
dc.description.degreeBSc/BA
dc.format.extent45
dc.identifier.urihttps://hdl.handle.net/2437/339735
dc.language.isoen
dc.rights.accessHozzáférhető a 2022 decemberi felsőoktatási törvénymódosítás értelmében.
dc.subjectfacial recognition
dc.subjectoneshot learning
dc.subjectopenset classification
dc.subjectcomputer vision
dc.subject.dspaceDEENK Témalista::Informatika::Számítógéptudomány
dc.titleExploring Open Set Classification for Facial Recognition Applications
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