Deep feature based efficient regularised ensemble for engagement recognition

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Over the years, open education in online environments, such as Massive Online Open Courses, has grown rapidly. While the trend is expected to bridge the educational gap among students, the new environment has also created new challenges such as the lack of feedback and difficulties in interaction. The authors propose an automated engagement recognition system to alleviate this problem, driven by the recent developments in computer vision and artificial neural networks. The authors' proposed system extracts deep features from a facial image and employs a combination of multiple regularised shallow networks to recognise engagement. They verified the system in a public data set. The proposed system has faster learning speed and better accuracy than single deep network based approaches do.
Publisher
INST ENGINEERING TECHNOLOGY-IET
Issue Date
2019-11
Language
English
Article Type
Article
Citation

ELECTRONICS LETTERS, v.55, no.24, pp.1281 - 1282

ISSN
0013-5194
DOI
10.1049/el.2019.2783
URI
http://hdl.handle.net/10203/270285
Appears in Collection
CS-Journal Papers(저널논문)
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