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DC Field | Value | Language |
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dc.contributor.author | Kornprom Pikulkaew | en_US |
dc.contributor.author | Ekkarat Boonchieng | en_US |
dc.contributor.author | Waraporn Boonchieng | en_US |
dc.contributor.author | Varin Chouvatut | en_US |
dc.date.accessioned | 2021-01-27T04:17:05Z | - |
dc.date.available | 2021-01-27T04:17:05Z | - |
dc.date.issued | 2021-01-01 | en_US |
dc.identifier.issn | 21945365 | en_US |
dc.identifier.issn | 21945357 | en_US |
dc.identifier.other | 2-s2.0-85091919743 | en_US |
dc.identifier.other | 10.1007/978-981-15-5859-7_42 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85091919743&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/71895 | - |
dc.description.abstract | © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021. Recent evidence has appeared that major enhancements in patient results can be increased by the periodical observing patient pain levels by medical staff in hospitals. Nevertheless, owing to the responsibility and pressure that the staffs have, this kind of observation has been complicated to withstand; thus, a system that works automatically could be the solution. Using an automatic facial expression system to detect pain which pain can be defined via several facial action units (AUs). To simplify pain detection using deep learning, data were collected from the UNBC database, which contains sequences of images that show participants’ faces while they were doing an arrangement of movement-of-motion tests. To improve pain detection using facial expressions, this research proposes a pain detection technique that uses deep learning. Finally, the resulting of the experiment will be compared with the self-reports, and doctors will be asked to evaluate the system. | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Engineering | en_US |
dc.title | Pain detection using deep learning with evaluation system | en_US |
dc.type | Book Series | en_US |
article.title.sourcetitle | Advances in Intelligent Systems and Computing | en_US |
article.volume | 1184 | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
article.stream.affiliations | Center of Excellence in Community Health Informatics | en_US |
Appears in Collections: | CMUL: Journal Articles |
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