97 citations · 239 across the 26 of their papers we have counts for
6 papers · 1 filter
A Sub-Layered Hierarchical Pyramidal Neural Architecture for Facial Expression Recognition
Henrique Siqueira, Pablo Barros, Sven Magg +2
In domains where computational resources and labeled data are limited, such as in robotics, deep networks with millions of weights might not be the optimal solution. In this paper,…
Tell Me Why You Feel That Way: Processing Compositional Dependency for Tree-LSTM Aspect Sentiment Triplet Extraction (TASTE)
A. Sutherland, S. Bensch, T. Hellström +2
Sentiment analysis has transitioned from classifying the sentiment of an entire sentence to providing the contextual information of what targets exist in a sentence, what sentiment…
Disambiguating Affective Stimulus Associations for Robot Perception and Dialogue
Henrique Siqueira, Alexander Sutherland, Pablo Barros +3
Effectively recognising and applying emotions to interactions is a highly desirable trait for social robots. Implicitly understanding how subjects experience different kinds of act…
An Ensemble with Shared Representations Based on Convolutional Networks for Continually Learning Facial Expressions
Henrique Siqueira, Pablo Barros, Sven Magg +1
Social robots able to continually learn facial expressions could progressively improve their emotion recognition capability towards people interacting with them. Semi-supervised le…
Leveraging Recursive Processing for Neural-Symbolic Affect-Target Associations
A. Sutherland, S. Magg, S. Wermter
Explaining the outcome of deep learning decisions based on affect is challenging but necessary if we expect social companion robots to interact with users on an emotional level. In…
Analyzing the Influence of Dataset Composition for Emotion Recognition
A. Sutherland, S. Magg, C. Weber +1
Recognizing emotions from text in multimodal architectures has yielded promising results, surpassing video and audio modalities under certain circumstances. However, the method by…