AIMC Topic: Emotions

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3D-BCLAM: A Lightweight Neurodynamic Model for Assessing Student Learning Effectiveness.

Sensors (Basel, Switzerland)
Evaluating students' learning effectiveness is of great importance for gaining a deeper understanding of the learning process, accurately diagnosing learning barriers, and developing effective teaching strategies. Emotion, as a key factor influencing...

An automated approach to identify sarcasm in low-resource language.

PloS one
Sarcasm detection has emerged due to its applicability in natural language processing (NLP) but lacks substantial exploration in low-resource languages like Urdu, Arabic, Pashto, and Roman-Urdu. While fewer studies identifying sarcasm have focused on...

Eeg based smart emotion recognition using meta heuristic optimization and hybrid deep learning techniques.

Scientific reports
In the domain of passive brain-computer interface applications, the identification of emotions is both essential and formidable. Significant research has recently been undertaken on emotion identification with electroencephalogram (EEG) data. The aim...

Tensor dictionary-based heterogeneous transfer learning to study emotion-related gender differences in brain.

Neural networks : the official journal of the International Neural Network Society
In practice, collecting auxiliary labeled data with same feature space from multiple domains is difficult. Thus, we focus on the heterogeneous transfer learning to address the problem of insufficient sample sizes in neuroimaging. Viewing subjects, ti...

Hybrid Network Using Dynamic Graph Convolution and Temporal Self-Attention for EEG-Based Emotion Recognition.

IEEE transactions on neural networks and learning systems
The electroencephalogram (EEG) signal has become a highly effective decoding target for emotion recognition and has garnered significant attention from researchers. Its spatial topological and time-dependent characteristics make it crucial to explore...

Artificial intelligence chatbots versus traditional medical resources for patient education on "Labor Epidurals": an evaluation of accuracy, emotional tone, and readability.

International journal of obstetric anesthesia
BACKGROUND: Labor epidural analgesia is a widely used method for pain relief in childbirth, yet information accessibility for expectant mothers remains a challenge. Artificial intelligence (AI) chatbots like Chat Generative Pre-Trained Transformer (C...

Improving care for amyotrophic lateral sclerosis with artificial intelligence and affective computing.

Journal of the neurological sciences
BACKGROUND: Patients with ALS often face difficulties expressing emotions due to impairments in facial expression, speech, body language, and cognitive function. This study aimed to develop non-invasive AI tools to detect and quantify emotional respo...

Neural correlates of empathy in donation decisions: Insights from EEG and machine learning.

Neuroscience
Empathy is central to individual and societal well-being. Numerous studies have examined how trait of empathy affects prosocial behavior. However, little studies explored the psychological and neural mechanisms by which different dimensions of trait ...

Improved facial emotion recognition model based on a novel deep convolutional structure.

Scientific reports
Facial Emotion Recognition (FER) is a very challenging task due to the varying nature of facial expressions, occlusions, illumination, pose variations, cultural and gender differences, and many other aspects that cause a drastic degradation in qualit...

A Novel and Powerful Dual-Stream Multi-Level Graph Convolution Network for Emotion Recognition.

Sensors (Basel, Switzerland)
Emotion recognition enables machines to more acutely perceive and understand users' emotional states, thereby offering more personalized and natural interactive experiences. Given the regularity of the responses of brain activity to human cognitive p...