AIMC Topic: Emotions

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Validating Emotion Analysis on Social Media Text for Detecting Psychological Distress: A Cross-Sectional Survey.

Issues in mental health nursing
This study investigates the relationship between self-reported psychological distress and emotions in social media posts, using a deep learning-based emotion analysis model. A cross-sectional design was used, collecting data from Instagram and Thread...

AdamGraph: Adaptive Attention-Modulated Graph Network for EEG Emotion Recognition.

IEEE transactions on cybernetics
The underlying time-variant and subject-specific brain dynamics lead to inconsistent distributions in electroencephalogram (EEG) topology and representations within and between individuals. However, current works primarily align the distributions of ...

Using deep learning models to decode emotional states in horses.

Scientific reports
In this study, we explore machine learning models for predicting emotional states in ridden horses. We manually label the images to train the models in a supervised manner. We perform data exploration and use different cropping methods, mainly based ...

Exploring the potential of large language models to understand interpersonal emotion regulation strategies from narratives.

Emotion (Washington, D.C.)
Interpersonal emotion regulation involves using diverse strategies to influence others' emotions, commonly assessed with questionnaires. However, this method may be less effective for individuals with limited literacy or introspection skills. To addr...

Understanding Robot Gesture Perception in Children with Autism Spectrum Disorder during Human-Robot Interaction.

International journal of neural systems
Social robots are increasingly being used in therapeutic contexts, especially as a complement in the therapy of children with Autism Spectrum Disorder (ASD). Because of this, the aim of this study is to understand how children with ASD perceive and i...

Driver facial emotion tracking using an enhanced residual network with weighted fusion of channel and spatial attention.

Scientific reports
Facial expression recognition (FER) plays a crucial role in interpreting human emotions and intentions in real-life applications, such as advanced driver assistance systems. However, it faces challenges due to subtle facial variations, environmental ...

A multi-domain constraint learning system inspired by adaptive cognitive graphs for emotion recognition.

Neural networks : the official journal of the International Neural Network Society
Neuroscience shows that the brain stimulated by external information can induce functional responses to emotions, which can be measured and analyzed by electroencephalogram (EEG). Most existing works focus on extracting specific spatial topological i...

Personalized Health Prediction AI Models Using Transfer Learning and Strategic Overfitting on Wearable Device Data.

Journal of medical systems
The increasing availability of wearable device data provides an opportunity for developing personalized models for health monitoring and condition prediction. Unlike conventional approaches that rely on pooled data from diverse individuals, our study...

Speech emotion recognition with light weight deep neural ensemble model using hand crafted features.

Scientific reports
Automatic emotion detection has become crucial in various domains, such as healthcare, neuroscience, smart home technologies, and human-computer interaction (HCI). Speech Emotion Recognition (SER) has attracted considerable attention because of its p...

CNN-LSTM based emotion recognition using Chebyshev moment and K-fold validation with multi-library SVM.

PloS one
Human emotions are not necessarily tends to produce right facial expressions as there is no well defined connection between them. Although, human emotions are spontaneous, their facial expressions depend a lot on their mental and psychological capaci...