AIMC Topic: Automated Facial Recognition

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Facial Expression Recognition for Healthcare Monitoring Systems Using Neural Random Forest.

IEEE journal of biomedical and health informatics
Facial expressions vary with different health conditions, making a facial expression recognition (FER) system valuable within a healthcare framework. Achieving accurate recognition of facial expressions is a considerable challenge due to the difficul...

Artificial intelligence facial recognition of obstructive sleep apnea: a Bayesian meta-analysis.

Sleep & breathing = Schlaf & Atmung
PURPOSE: Conventional obstructive sleep apnea (OSA) diagnosis via polysomnography can be costly and inaccessible. Recent advances in artificial intelligence (AI) have enabled the use of craniofacial photographs to diagnose OSA. This meta-analysis aim...

Multi-loss, feature fusion and improved top-two-voting ensemble for facial expression recognition in the wild.

Neural networks : the official journal of the International Neural Network Society
Facial expression recognition (FER) in the wild is a challenging pattern recognition task affected by the images' low quality and has attracted broad interest in computer vision. Existing FER methods failed to obtain sufficient accuracy to support th...

MCCA-VNet: A Vit-Based Deep Learning Approach for Micro-Expression Recognition Based on Facial Coding.

Sensors (Basel, Switzerland)
In terms of facial expressions, micro-expressions are more realistic than macro-expressions and provide more valuable information, which can be widely used in psychological counseling and clinical diagnosis. In the past few years, deep learning metho...

Towards generalizable face forgery detection via mitigating spurious correlation.

Neural networks : the official journal of the International Neural Network Society
The continuous advancement of face forgery techniques has caused a series of trust crises, posing a significant menace to information security and personal privacy. In response, deep learning is being employed to develop effective detection methods t...

RF sensing enabled tracking of human facial expressions using machine learning algorithms.

Scientific reports
Automatic analysis of facial expressions has emerged as a prominent research area in the past decade. Facial expressions serve as crucial indicators for understanding human behavior, enabling the identification and assessment of positive and negative...

Facial Image expression recognition and prediction system.

Scientific reports
Facial expression recognition system is an advanced technology that allows machines to recognize human emotions based on their facial expressions. In order to develop a robust prediction model, this research work proposes three distinct architectural...

CSTAN: A Deepfake Detection Network with CST Attention for Superior Generalization.

Sensors (Basel, Switzerland)
With the advancement of deepfake forgery technology, highly realistic fake faces have posed serious security risks to sensor-based facial recognition systems. Recent deepfake detection models mainly use binary classification models based on deep lear...

Diagnosis and Screening of Velocardiofacial Syndrome by Evaluating Facial Photographs Using a Deep Learning-Based Algorithm.

Plastic and reconstructive surgery
BACKGROUND: Early detection of rare genetic diseases, including velocardiofacial syndrome (VCFS), is essential for patient well-being. However, the rarity of these diseases and limited clinical experience of physicians make diagnosis challenging. Dee...

Enhancing Facial Expression Recognition through Light Field Cameras.

Sensors (Basel, Switzerland)
In this paper, we study facial expression recognition (FER) using three modalities obtained from a light field camera: sub-aperture (SA), depth map, and all-in-focus (AiF) images. Our objective is to construct a more comprehensive and effective FER s...