EMOTION ESTIMATION THROUGH 3D CONVOLUTIONAL NEURAL NETWORK IN VIDEOS

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dc.contributor.author	Rakhimzhanova, Jamilya
dc.date.accessioned	2024-06-13T11:48:31Z
dc.date.available	2024-06-13T11:48:31Z
dc.date.issued	2024-04-29
dc.identifier.citation	Rakhimzhanova, J. (2024). Emotion Estimation Through 3D Convolutional Neural Network in Videos. Nazarbayev University School of Engineering and Digital Sciences	en_US
dc.identifier.uri	http://nur.nu.edu.kz/handle/123456789/7864
dc.description.abstract	The 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.language.iso	en	en_US
dc.publisher	Nazarbayev University School of Engineering and Digital Sciences	en_US
dc.rights	Attribution-NonCommercial-ShareAlike 3.0 United States	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-sa/3.0/us/	*
dc.subject	Type of access: Restricted	en_US
dc.subject	Emotion Recognition	en_US
dc.title	EMOTION ESTIMATION THROUGH 3D CONVOLUTIONAL NEURAL NETWORK IN VIDEOS	en_US
dc.type	Bachelor's thesis	en_US
workflow.import.source	science