AIMC Topic: Emotions

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Emotion Classification Based on Pulsatile Images Extracted from Short Facial Videos via Deep Learning.

Sensors (Basel, Switzerland)
Most human emotion recognition methods largely depend on classifying stereotypical facial expressions that represent emotions. However, such facial expressions do not necessarily correspond to actual emotional states and may correspond to communicati...

Exploring the use of ChatGPT to analyze student course evaluation comments.

BMC medical education
BACKGROUND: Since the release of ChatGPT, numerous positive applications for this artificial intelligence (AI) tool in higher education have emerged. Faculty can reduce workload by implementing the use of AI. While course evaluations are a common too...

A multi-featured expression recognition model incorporating attention mechanism and object detection structure for psychological problem diagnosis.

Physiology & behavior
Expression is the main method for judging the emotional state and psychological condition of the human body, and the prediction of changes in facial expressions can effectively determine the mental health of a person, thus avoiding serious psychologi...

MSLTE: multiple self-supervised learning tasks for enhancing EEG emotion recognition.

Journal of neural engineering
. The instability of the EEG acquisition devices may lead to information loss in the channels or frequency bands of the collected EEG. This phenomenon may be ignored in available models, which leads to the overfitting and low generalization of the mo...

Positive Emotional Responses to Socially Assistive Robots in People With Dementia: Pilot Study.

JMIR aging
BACKGROUND: Interventions and care that can evoke positive emotions and reduce apathy or agitation are important for people with dementia. In recent years, socially assistive robots used for better dementia care have been found to be feasible. Howeve...

Enhancing cross-subject EEG emotion recognition through multi-source manifold metric transfer learning.

Computers in biology and medicine
Transfer learning (TL) has demonstrated its efficacy in addressing the cross-subject domain adaptation challenges in affective brain-computer interfaces (aBCI). However, previous TL methods usually use a stationary distance, such as Euclidean distanc...

Physiological data for affective computing in HRI with anthropomorphic service robots: the AFFECT-HRI data set.

Scientific data
In human-human and human-robot interaction, the counterpart influences the human's affective state. Contrary to humans, robots inherently cannot respond empathically, meaning non-beneficial affective reactions cannot be mitigated. Thus, to create a r...

Does Pollyanna hypothesis hold true in death narratives? A sentiment analysis approach.

Acta psychologica
Pollyanna hypothesis claims that human beings have a universal tendency to use positive words more frequently and broadly than negative words. The present study aims to test Pollyanna hypothesis in medical death narratives at both lexical and text le...

MV-SHIF: Multi-view symmetric hypothesis inference fusion network for emotion-cause pair extraction in documents.

Neural networks : the official journal of the International Neural Network Society
Emotion-cause pair extraction (ECPE) is a challenging task that aims to automatically identify pairs of emotions and their causes from documents. The difficulty of ECPE lies in distinguishing valid emotion-cause pairs from many irrelevant ones. Most ...

A Comparison Study of Deep Learning Methodologies for Music Emotion Recognition.

Sensors (Basel, Switzerland)
Classical machine learning techniques have dominated Music Emotion Recognition. However, improvements have slowed down due to the complex and time-consuming task of handcrafting new emotionally relevant audio features. Deep learning methods have rece...