Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Judith Azcarraga"'
Autor:
Jocelynn Cu, Cedric Jose Herrera, Jennifer C. Ureta, Klint John Poliquit, Judith Azcarraga, Sean Latrelle Bravo, Joanna Pauline Rivera, Edward Carlo Valdez
Publikováno v:
ICAART (2)
Autor:
Judith Azcarraga, Maria Jeseca Baculo
Publikováno v:
SMC
Facial landmarks may be used to localize the movement of facial muscles that help identify an emotion. It is important that these points are appropriately represented to achieve a successful emotion recognition rate. In this paper, the extraction of
Publikováno v:
International Journal of Distance Education Technologies. 11:1-15
Brainwaves (EEG signals) and mouse behavior information are shown to be useful in predicting academic emotions, such as confidence, excitement, frustration and interest. Twenty five college students were asked to use the Aplusix math learning softwar
Publikováno v:
Neural Information Processing ISBN: 9783319466804
ICONIP (4)
ICONIP (4)
Gender-specific classifiers are shown to outperform general classifiers. In calibrated experiments designed to demonstrate this, two sets of data were used to build male-specific and female-specific classifiers. The first dataset is used to predict v
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::015de3ac984fb190c01e1b577feadfbd
https://doi.org/10.1007/978-3-319-46681-1_59
https://doi.org/10.1007/978-3-319-46681-1_59
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783642326943
PRICAI
PRICAI
This research presents how the level of academic emotions such as confidence, excitement, frustration and interest, may be predicted based on brainwaves and mouse behaviour, while taking into account the student's personality. Twenty five (25) colleg
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::154c0ad0bc553b250c5b0c638fb35304
https://doi.org/10.1007/978-3-642-32695-0_64
https://doi.org/10.1007/978-3-642-32695-0_64
Publikováno v:
KSE
The academic emotion of learners is difficult to predict using EEG data, unless these brainwaves data undergo some extensive pre-processing operations. However, we show some evidence that it can be predicted somewhat more accurately for certain perso