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pub:research [2021/01/07 10:19] – MRC2020 published kkutt | pub:research [2021/02/02 18:50] – ICAISC2020 added kkutt | ||
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===== Papers ===== | ===== Papers ===== | ||
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+ | === Sensors2021 === | ||
+ | * K. Kutt, D. Drążyk, S. Bobek, and G. J. Nalepa, " | ||
+ | * DOI: [[https:// | ||
+ | * [[https:// | ||
+ | * ++Abstract | In this article, we propose using personality assessment as a way to adapt affective intelligent systems. This psychologically-grounded mechanism will divide users into groups that differ in their reactions to affective stimuli for which the behaviour of the system can be adjusted. In order to verify the hypotheses, we conducted an experiment on 206 people, which consisted of two proof-of-concept demonstrations: | ||
+ | |||
+ | === ICAISC2020 === | ||
+ | * S. Bobek, M. M. Tragarz, M. Szelążek, and G. J. Nalepa, " | ||
+ | * DOI: [[https:// | ||
+ | * [[https:// | ||
+ | * ++Abstract | Development of models for emotion detection is often based on the use of machine learning. However, it poses practical challenges, due to the limited understanding of modeling of emotions, as well as the problems regarding measurements of bodily signals. In this paper we report on our recent work on improving such models, by the use of explainable AI methods. We are using the BIRAFFE data set we created previously during our own experiment in affective computing.++ | ||
=== HAIIW2020 === | === HAIIW2020 === |