@inProceedings{
 title = {Emotion detection},
 type = {inProceedings},
 year = {2017},
 identifiers = {[object Object]},
 keywords = {emotion recognition,technologies},
 pages = {1-8},
 websites = {http://dl.acm.org/citation.cfm?doid=3123818.3123852},
 publisher = {ACM Press},
 city = {New York, New York, USA},
 id = {22e622e3-974a-3ac5-a062-575e16fb8b9c},
 created = {2017-09-28T08:59:07.992Z},
 file_attached = {true},
 profile_id = {7968b917-928b-32cd-82d9-e9264751b764},
 last_modified = {2018-05-17T15:22:57.758Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Garcia-Garcia2017},
 folder_uuids = {2a301708-2857-4f2a-9682-8a8311c6854b},
 private_publication = {false},
 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.},
 bibtype = {inProceedings},
 author = {Garcia-Garcia, Jose Maria and Penichet, Victor M R and Lozano, Maria D},
 booktitle = {Proceedings of the XVIII International Conference on Human Computer Interaction - Interacción '17}
}

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