This research applies unsupervised learning on a large original dataset of horses in the wild to identify previously unidentified horse emotions. We construct a novel, high-quality, diverse dataset of 3929 images consisting of five wild horse breeds ...
Neural networks : the official journal of the International Neural Network Society
40010290
Emotion recognition plays a key role in the field of human-computer interaction. Classifying and predicting human emotions using electroencephalogram (EEG) signals has consistently been a challenging research area. Recently, with the increasing appli...
This study explores the link between the emotion "guilt" and human EEG data, and investigates the influence of gender differences on the expression of guilt and neutral emotions in response to visual stimuli. Additionally, the stimuli used in the stu...
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...
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, ...
As educational environments become more diverse, adaptive technologies like social robots hold promise for providing individual support to learners. This study investigated the role of adaptive teaching of a robot on students' learning outcomes, emot...
Neural networks : the official journal of the International Neural Network Society
39978138
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...
Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
39957550
AIM(S): To determine the correlation between preoperative health education and the emotions of lung cancer patients, artificial intelligence software was used.
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...