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FaceEngage: Robust Estimation of Gameplay Engagement from Real-World Front-Facing Videos
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | FaceEngage: Robust Estimation of Gameplay Engagement from Real-World Front-Facing Videos. |
| 개인저자 | Chen, Xu. |
| 단체저자명 | Rice University. Electrical and Computer Engineering. |
| 발행사항 | [S.l.]: Rice University., 2019. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2019. |
| 형태사항 | 62 p. |
| 기본자료 저록 | Dissertations Abstracts International 83-03A. Dissertation Abstract International |
| ISBN | 9798535520100 |
| 학위논문주기 | Thesis (Ph.D.)--Rice University, 2019. |
| 일반주기 |
Source: Dissertations Abstracts International, Volume: 83-03, Section: A.
Advisor: Sabharwal, Ashutosh. |
| 이용제한사항 | This item must not be sold to any third party vendors. |
| 일반주제명 | Computer science. Electrical engineering. Physiology. Accuracy. Deep learning. Datasets. Audiences. Video recordings. Student writing. Questionnaires. Labeling. Cognitive load. Electroencephalography. Games. Aesthetics. Psychologists. Velocity. Cameras. Absolute pitch. Experiments. Sensors. Data collection. Methods. Algorithms. Annotations. Heart rate. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
