AIMC Topic: Emotions

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An Artificial Intelligence Model for Sensing Affective Valence and Arousal from Facial Images.

Sensors (Basel, Switzerland)
Artificial intelligence (AI) models can sense subjective affective states from facial images. Although recent psychological studies have indicated that dimensional affective states of valence and arousal are systematically associated with facial expr...

Advancing Emotionally Aware Child-Robot Interaction with Biophysical Data and Insight-Driven Affective Computing.

Sensors (Basel, Switzerland)
This paper investigates the integration of affective computing techniques using biophysical data to advance emotionally aware machines and enhance child-robot interaction (CRI). By leveraging interdisciplinary insights from neuroscience, psychology, ...

MemoCMT: multimodal emotion recognition using cross-modal transformer-based feature fusion.

Scientific reports
Speech emotion recognition has seen a surge in transformer models, which excel at understanding the overall message by analyzing long-term patterns in speech. However, these models come at a computational cost. In contrast, convolutional neural netwo...

A Tutorial on the Use of Artificial Intelligence Tools for Facial Emotion Recognition in R.

Multivariate behavioral research
Automated detection of facial emotions has been an interesting topic for multiple decades in social and behavioral research but is only possible very recently. In this tutorial, we review three popular artificial intelligence based emotion detection ...

Memristor-based circuit design of interweaving mechanism of emotional memory in a hippocamp-brain emotion learning model.

Neural networks : the official journal of the International Neural Network Society
Endowing robots with human-like emotional and cognitive abilities has garnered widespread attention, driving deep investigations into the complexities of these processes. However, few studies have examined the intricate circuits that govern the inter...

Face readers.

Science (New York, N.Y.)
Artificial intelligence is becoming better than humans at scanning animals' faces for signs of stress and pain. Are more complex emotions next?

The cathartic dream: Using a large language model to study a new type of functional dream in healthy and clinical populations.

Journal of sleep research
According to some theories of emotion regulation, dreams could modify negative emotions and ultimately reduce their intensity. We introduce here the idea of cathartic dream, a specific and separate type of emotional dream, which is characterized by a...

Towards a latent space cartography of subjective experience in mental health.

Psychiatry and clinical neurosciences
AIMS: The way that individuals subjectively experience the world greatly influences their own mental well-being. However, it remains a considerable challenge to precisely characterize the breadth and depth of such experiences. One persistent problem ...

Machine learning reveals sex differences in distinguishing between conduct-disordered and neurotypical youth based on emotion processing dysfunction.

BMC psychiatry
BACKGROUND: Theoretical models of conduct disorder (CD) highlight that deficits in emotion recognition, learning, and regulation play a pivotal role in CD etiology. With CD being more prevalent in boys than girls, various theories aim to explain this...

TF-BERT: Tensor-based fusion BERT for multimodal sentiment analysis.

Neural networks : the official journal of the International Neural Network Society
Multimodal Sentiment Analysis (MSA) has gained significant attention due to the limitations of unimodal sentiment recognition in complex real-world applications. Traditional approaches typically focus on using the Transformer for fusion. However, the...