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Found 5 papers, 1 papers with code
Accommodating Missing Modalities in Time-Continuous Multimodal Emotion Recognition
Decades of research indicate that emotion recognition is more effective when drawing information from multiple modalities.
A Hierarchical Framework for Collaborative Artificial Intelligence
We propose a hierarchical framework for collaborative intelligent systems.
Transformer-Based Self-Supervised Learning for Emotion Recognition
We gathered several ECG datasets with no labels of emotion to pre-train our model, which we then fine-tuned for emotion recognition on the AMIGOS dataset.
Recognizing Manipulation Actions from State-Transformations
We start by defining a state transition matrix that maps action labels into a pre-state and a post-state.
Multimodal Observation and Interpretation of Subjects Engaged in Problem Solving
In this paper we present the first results of a pilot experiment in the capture and interpretation of multimodal signals of human experts engaged in solving challenging chess problems.
