AIMC Topic: Facial Expression

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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...

Day-to-day dynamics of facial emotion expressions in posttraumatic stress disorder.

Journal of affective disorders
Facial expressions are an essential component of emotions that may reveal mechanisms maintaining posttraumatic stress disorder (PTSD). However, most research on emotions in PTSD has relied on self-reports, which only capture subjective affect. The fe...

Neural network-based ensemble approach for multi-view facial expression recognition.

PloS one
In this paper, we developed a pose-aware facial expression recognition technique. The proposed technique employed K nearest neighbor for pose detection and a neural network-based extended stacking ensemble model for pose-aware facial expression recog...

Artificial Intelligence in Facial Palsy Treatment: A Systematic Review and Recommendations.

Plastic and reconstructive surgery
BACKGROUND: Artificial intelligence (AI) is rapidly advancing and increasingly applied in facial palsy research. However, there is no comprehensive review to guide surgeons on AI-based facial assessment tools. Although photographic standards exist, v...

DCAlexNet: Deep coupled AlexNet for micro facial expression recognition based on double face images.

Computers in biology and medicine
Facial Micro-Expression Recognition (FER) presents challenges due to individual variations in emotional intensity and the complexity of feature extraction. While apex frames offer valuable emotional information, their precise role in FER remains uncl...

Overconfident, but angry at least. AI-Based investigation of facial emotional expressions and self-assessment bias in human adults.

BMC psychology
Metacognition and facial emotional expressions both play a major role in human social interactions [1, 2] as inner narrative and primary communicational display, and both are limited by self-monitoring, control and their interaction with personal and...

Disclosing neonatal pain in real-time: AI-derived pain sign from continuous assessment of facial expressions.

Computers in biology and medicine
This study introduces an AI-derived pain sign for continuous neonatal pain assessment, addressing the limitations of existing pain scales and computational approaches. Traditional pain scales, though widely used, are hindered by inter-rater variabili...

Application of Multiple Deep Learning Architectures for Emotion Classification Based on Facial Expressions.

Sensors (Basel, Switzerland)
Facial expression recognition (FER) is essential for discerning human emotions and is applied extensively in big data analytics, healthcare, security, and user experience enhancement. This study presents a comprehensive evaluation of ten state-of-the...

Machine learning classification of active viewing of pain and non-pain images using EEG does not exceed chance in external validation samples.

Cognitive, affective & behavioral neuroscience
Previous research has demonstrated that machine learning (ML) could not effectively decode passive observation of neutral versus pain photographs by using electroencephalogram (EEG) data. Consequently, the present study explored whether active viewin...

A Multimodal Pain Sentiment Analysis System Using Ensembled Deep Learning Approaches for IoT-Enabled Healthcare Framework.

Sensors (Basel, Switzerland)
This study introduces a multimodal sentiment analysis system to assess and recognize human pain sentiments within an Internet of Things (IoT)-enabled healthcare framework. This system integrates facial expressions and speech-audio recordings to evalu...