Please use this identifier to cite or link to this item: https://dspace.univ-ouargla.dz/jspui/handle/123456789/36901
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dc.contributor.authorCHAA, Mourad-
dc.contributor.authorHAMDI, Aya-
dc.contributor.authorHACINI, Ikram-
dc.contributor.authorBENHAOUED, Nadra-
dc.date.accessioned2024-09-29T10:35:41Z-
dc.date.available2024-09-29T10:35:41Z-
dc.date.issued2024-
dc.identifier.citationFACULTE DES NOUVELLES TECHNOLOGIES DE L'INFORMATIQUE ET DE LA COMMUNICATIONen_US
dc.identifier.urihttps://dspace.univ-ouargla.dz/jspui/handle/123456789/36901-
dc.descriptionSystem of telecommunications.en_US
dc.description.abstractDwayadz is a health application that uses machine and deep learning techniques to quickly and accurately classify medications. The application allows users to capture images of medications using their smartphones, analyzing them and classifying them. The research focuses on the development, collection of data, and evaluation of the performance of machine and deep learning models. The study also addresses challenges such as classification accuracy due to the similarity of certain medications and data protection and user privacy. The goal is to improve the application's performance, expand the database used in training, and improve the user interface.en_US
dc.description.sponsorshipDepartment of Electronics and Telecommunicationsen_US
dc.language.isoenen_US
dc.publisherUNIVERSITY KASDI MERBAH OUARGLAen_US
dc.subjectMachine Learning (ML)en_US
dc.subjectDeep Learning (DL)en_US
dc.subjectImage Classificationen_US
dc.subjectConvolutional Neuralen_US
dc.subjectNetwork (CNN)en_US
dc.titleA platform for searching and classifying medicinesen_US
dc.typeThesisen_US
Appears in Collections:Département d'Electronique et des Télécommunications - Master

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