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Investigation of accurate, fast, robust, neural gesture recognition involving a sequential approach

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dc.contributor.advisorWeir, Michael
dc.contributor.authorAlmuallem, Zahida
dc.coverage.spatial467en_US
dc.date.accessioned2023-08-18T14:10:41Z
dc.date.available2023-08-18T14:10:41Z
dc.date.issued2023-11-28
dc.identifier.urihttps://hdl.handle.net/10023/28201
dc.description.abstractAbstract redacteden_US
dc.description.sponsorship"I would like to show my gratitude to my employer, the Department of Computer Science at King Saud University, for permitting me to study leave and granting a scholarship to pursue my PhD study. Also, I would like to thank them for their support and understanding, especially during the Covid-19 pandemic. This work was not possible without their support as this work was fully supported by King Saud University (college of computer and information science)."--Acknowledgementsen
dc.language.isoenen_US
dc.relationLocal minima Benchmark Problems and two letters dataset (thesis data). Almuallem, Z., University of St Andrews, 14 Aug 2025. DOI: https://doi.org/10.17630/b604b5ae-ec6d-4b0a-b050-a4bbf80b948ben
dc.relation.urihttps://doi.org/10.17630/b604b5ae-ec6d-4b0a-b050-a4bbf80b948b
dc.titleInvestigation of accurate, fast, robust, neural gesture recognition involving a sequential approachen_US
dc.typeThesisen_US
dc.contributor.sponsorKing Saud Universityen_US
dc.type.qualificationlevelDoctoralen_US
dc.type.qualificationnamePhD Doctor of Philosophyen_US
dc.publisher.institutionThe University of St Andrewsen_US
dc.rights.embargodate2025-08-14
dc.rights.embargoreasonThesis restricted in accordance with University regulations. Restricted until 14th August 2025en
dc.identifier.doihttps://doi.org/10.17630/sta/583


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