Affective computing stands at the forefront of artificial intelligence (AI), seeking to imbue
machines with the ability to comprehend and respond to human emotions. Central to this …

Audio-visual emotion recognition is the research of identifying human emotional states by
combining the audio modality and the visual modality simultaneously, which plays an …

When a multi-modal affective analysis model generalizes from a bimodal task to a trimodal
or multi-modal task, it is usually transformed into a hierarchical fusion model based on every …

Emotion recognition based on text–audio modalities is the core technology for transforming
a graphical user interface into a voice user interface, and it plays a vital role in natural …

Human–machine interaction covers a range of applications in which machines should
understand humans' commands and predict their behavior. Humans commonly change their …

We consider the problem of identifying universal low-dimensional features from high-
dimensional data for inference tasks in settings involving learning. For such problems, we …

Learning with multiple modalities is crucial for automated brain tumor segmentation from
magnetic resonance imaging data. Explicitly optimizing the common information shared …

Audio-visual emotion recognition is important for human-machine interaction systems by
combining the information of audio and visual modalities. Although great progress has been …

Audio-visual emotion recognition aims to distinguish human emotional states by integrating
the audio and visual data acquired in the expression of emotions. It is crucial for facilitating …

Dimensional emotion recognition research is an important branch of affective computing,
which uses continuous values to represent complex human emotions. In this study, we …