Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/156739
Title: Facial emotion recognition using vision transformer
Authors: Low, Triston Zhi Yang
Keywords: Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Low, T. Z. Y. (2022). Facial emotion recognition using vision transformer. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/156739
Abstract: The facial emotion recognition task (FER) has gained a lot of attention in the recent years due to the advancement in deep learning and artificial intelligence. The vast number of facial emotion databases made available online also encouraged research and development in this area. Researchers in the field are experimenting various techniques which allow the computer to extract facial features, study them, to build highly accurate prediction models. Analysis and continuous improvements to these image recognition models have produced exceptional results for FER tasks. The aim of this project is to explore a vision transformer deep learning model for the FER task. The proposed model is evaluated on 2 publicly available databases and analysis is done at the different stages of the experiment.
URI: https://hdl.handle.net/10356/156739
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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