Enhanced deep learning predictive modelling approaches for pain intensity recognition from facial expression video images

Bargshady, Ghazal ORCID: https://orcid.org/0000-0002-2557-7928 (2020) Enhanced deep learning predictive modelling approaches for pain intensity recognition from facial expression video images. [Thesis (PhD/Research)]

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Ghazal Bargshady-PhD thesis-final.pdf
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Item Type: Thesis (PhD/Research)
Item Status: Live Archive
Additional Information: Doctor of Philosophy (PhD) thesis.
Faculty/School / Institute/Centre: Historic - Faculty of Business, Education, Law and Arts - School of Management and Enterprise (1 Jul 2013 - 17 Jan 2021)
Faculty/School / Institute/Centre: Historic - Faculty of Business, Education, Law and Arts - School of Management and Enterprise (1 Jul 2013 - 17 Jan 2021)
Supervisors: Soar, Jeffrey; Zhou, Xujuan; Deo, Ravinesh C.; Whittaker, Frank; Wang, Hua
Date Deposited: 18 Nov 2020 05:42
Last Modified: 21 Apr 2021 00:10
Uncontrolled Keywords: facial expression, deep learning, automatic pain detection, neural networks, computer vision, image processing
Fields of Research (2008): 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080105 Expert Systems
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080199 Artificial Intelligence and Image Processing not elsewhere classified
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080104 Computer Vision
Fields of Research (2020): 46 INFORMATION AND COMPUTING SCIENCES > 4603 Computer vision and multimedia computation > 460304 Computer vision
Identification Number or DOI: doi:10.26192/kjka-n867
URI: http://eprints.usq.edu.au/id/eprint/40117

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