首页|Studies from University of Quebec in Outaouais in the Area of Machine Learning D escribed (Optimizable Ensemble Regression for Arousal and Valence Predictions fr om Visual Features)
Studies from University of Quebec in Outaouais in the Area of Machine Learning D escribed (Optimizable Ensemble Regression for Arousal and Valence Predictions fr om Visual Features)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on artificial intelligenc e is the subject of a new report. According to news reporting originating from G atineau, Canada, by NewsRx correspondents, research stated, “The cognitive state of a person can be categorized using the Circumplex model of emotional states, a continuous model of two dimensions: arousal and valence. We exploit the Remote Collaborative and Affective Interactions (RECOLA) database, which includes audi o, video, and physiological recordings of interactions between human participant s to predict arousal and valance values using machine learning techniques.” Our news correspondents obtained a quote from the research from University of Qu ebec in Outaouais: “To allow learners to focus on the most relevant data, featur es are extracted from raw data. Such features can be predesigned or learned. Lea rned features are automatically learned and utilized by deep learning solutions. Predesigned features are calculated before machine learning and inputted into t he learner. Our previous work on video recordings focused on learned features. I n this paper, we expand our work onto predesigned visual features, extracted fro m video recordings. We process these features by applying time delay and sequenc ing, arousal/valence labelling, and shuffling and splitting. We then train and t est regressors to predict arousal and valence values.”
University of Quebec in OutaouaisGatin eauCanadaNorth and Central AmericaCyborgsEmerging TechnologiesMachine Learning
NETL
NSTL
