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Emotion detection: a technology review

Published: 25 September 2017 Publication History

Abstract

Emotion detection has become one of the most important aspects to consider in any project related to Affective Computing. Due to the almost endless applications of this new discipline, the development of emotion detection technologies has brought up as a quite profitable opportunity in the corporate sector. Many start-up enterprises have emerged in the last years, dedicated almost exclusively to a specific type of emotion detection technology. In this paper, we present a thorough review of current technologies to detect human emotions. To this end, we explore the different sources from which emotions can be read, along with existing technologies developed to recognize them. We also explore some application domains in which this technology has been applied. This survey has let us identify the strengths and shortcomings of current technology for emotion detection. We conclude the survey highlighting the aspects that requires further research and development.

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  • (2025)Customer emotion detection and analytics in hotel and tourism services using multi-label classificational models based on ensemble learningAnnals of Operations Research10.1007/s10479-024-06434-2Online publication date: 16-Jan-2025
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    cover image ACM Other conferences
    Interacción '17: Proceedings of the XVIII International Conference on Human Computer Interaction
    September 2017
    268 pages
    ISBN:9781450352291
    DOI:10.1145/3123818
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 25 September 2017

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    Author Tags

    1. affective computing
    2. emotion recognition
    3. technologies

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    • (2024)IMPROVING E-LEARNING BY FACIAL EXPRESSION ANALYSISApplied Computer Science10.35784/acs-2024-2020:2(126-137)Online publication date: 30-Jun-2024
    • (2024)Recognition of Human Facial Expressions through the Application of Emerging Neural NetworksInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology10.32628/CSEIT241061239210:6(1982-1994)Online publication date: 12-Dec-2024
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