EMOTION ESTIMATION THROUGH 3D CONVOLUTIONAL NEURAL NETWORK IN VIDEOS

dc.contributor.authorRakhimzhanova, Jamilya
dc.date.accessioned2024-06-13T11:48:31Z
dc.date.available2024-06-13T11:48:31Z
dc.date.issued2024-04-29
dc.description.abstractThe project aims to present the methods of emotion estimation with a use of convolutional neural networks (3DCNN). Recognizing human emotions allow us to create user friendly devices and allow for devices to respond effectively to user needs. One potential application is in the healthcare field. Tools with effective emotion recognition algorithms can be used to treat and diagnose patients with mental health conditions, such as anxiety or depression. In marketing, these tools can be used to adjust preferences to consumer wants as currently done by AI tools.en_US
dc.identifier.citationRakhimzhanova, J. (2024). Emotion Estimation Through 3D Convolutional Neural Network in Videos. Nazarbayev University School of Engineering and Digital Sciencesen_US
dc.identifier.urihttp://nur.nu.edu.kz/handle/123456789/7864
dc.language.isoenen_US
dc.publisherNazarbayev University School of Engineering and Digital Sciencesen_US
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/us/*
dc.subjectType of access: Restricteden_US
dc.subjectEmotion Recognitionen_US
dc.titleEMOTION ESTIMATION THROUGH 3D CONVOLUTIONAL NEURAL NETWORK IN VIDEOSen_US
dc.typeBachelor's thesisen_US
workflow.import.sourcescience

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