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Face and emotion recognition with neural networks on mobile devices: Practical implementation on different platforms

Abstract:

We propose a novel architecture for face and emotion recognition and discuss modifications for different types of mobile applications. Emotion recognition task is challenging due to the absence of large-scale datasets and non-uniform labelling. We propose easy-to-implement five class classification approach and suggest modifications for large-scale emotion recognition on three different platforms: desktop, mobile and VPU, and compare the resulting speed and performance. We demonstrate that ou...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/fg.2019.8756562

Authors


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Institution:
University of Oxford
Division:
SSD
Department:
Said Business School
Role:
Author
ORCID:
0000-0003-4853-9550
Publisher:
Institute of Electrical and Electronics Engineers Publisher's website
Journal:
14th IEEE International Conference on Automatic Face and Gesture Recognition Journal website
Host title:
2019 14th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2019)
Publication date:
2019-07-11
DOI:
Source identifiers:
1038554
ISBN:
9781728100890
Pubs id:
pubs:1038554
UUID:
uuid:38395ff9-be22-40d6-aac5-ef27958c5914
Local pid:
pubs:1038554
Deposit date:
2019-08-05

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