32 citations · 112 across the 31 of their papers we have counts for
7 papers · 1 filter
Assessing the Contribution of Semantic Congruency to Multisensory Integration and Conflict Resolution
Di Fu, Pablo Barros, German I. Parisi +4
The efficient integration of multisensory observations is a key property of the brain that yields the robust interaction with the environment. However, artificial multisensory perc…
A Deep Neural Model Of Emotion Appraisal
Pablo Barros, Emilia Barakova, Stefan Wermter
Emotional concepts play a huge role in our daily life since they take part into many cognitive processes: from the perception of the environment around us to different learning pro…
Towards Modeling the Interaction of Spatial-Associative Neural Network Representations for Multisensory Perception
German I. Parisi, Jonathan Tong, Pablo Barros +2
Our daily perceptual experience is driven by different neural mechanisms that yield multisensory interaction as the interplay between exogenous stimuli and endogenous expectations.…
An Affective Robot Companion for Assisting the Elderly in a Cognitive Game Scenario
Nikhil Churamani, Alexander Sutherland, Pablo Barros
Being able to recognize emotions in human users is considered a highly desirable trait in Human-Robot Interaction (HRI) scenarios. However, most contemporary approaches rarely atte…
The OMG-Emotion Behavior Dataset
Pablo Barros, Nikhil Churamani, Egor Lakomkin +3
This paper is the basis paper for the accepted IJCNN challenge One-Minute Gradual-Emotion Recognition (OMG-Emotion) by which we hope to foster long-emotion classification using neu…
A Neurorobotic Experiment for Crossmodal Conflict Resolution in Complex Environments
German I. Parisi, Pablo Barros, Di Fu +4
Crossmodal conflict resolution is crucial for robot sensorimotor coupling through the interaction with the environment, yielding swift and robust behaviour also in noisy conditions…
Expectation Learning for Adaptive Crossmodal Stimuli Association
Pablo Barros, German I. Parisi, Di Fu +2
The human brain is able to learn, generalize, and predict crossmodal stimuli. Learning by expectation fine-tunes crossmodal processing at different levels, thus enhancing our power…