AIMC Topic: Face

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An Artificial Intelligence Model for Sensing Affective Valence and Arousal from Facial Images.

Sensors (Basel, Switzerland)
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...

Can AI-assisted objective facial attractiveness scoring systems replace manual aesthetic evaluations? A comparative analysis of human and machine ratings.

Journal of plastic, reconstructive & aesthetic surgery : JPRAS
BACKGROUND: In clinical practice, attaining a genuinely objective evaluation of facial aesthetics has posed considerable challenges owing to the inherent subjectivity of human observers. Artificial intelligence (AI) technology has demonstrated signif...

Automated strabismus detection and classification using deep learning analysis of facial images.

Scientific reports
Strabismus, or eye misalignment, is a common condition affecting individuals of all ages. Early detection and accurate classification are essential for proper treatment and avoiding long-term complications. This research presents a new deep-learning-...

Identification of Intracranial Germ Cell Tumors Based on Facial Photos: Exploratory Study on the Use of Deep Learning for Software Development.

Journal of medical Internet research
BACKGROUND: Primary intracranial germ cell tumors (iGCTs) are highly malignant brain tumors that predominantly occur in children and adolescents, with an incidence rate ranking third among primary brain tumors in East Asia (8%-15%). Due to their insi...

Real-Time Driver Drowsiness Detection Using Facial Analysis and Machine Learning Techniques.

Sensors (Basel, Switzerland)
Drowsy driving poses a significant challenge to road safety worldwide, contributing to thousands of accidents and fatalities annually. Despite advancements in driver drowsiness detection (DDD) systems, many existing methods face limitations such as i...

3D face reconstruction for maxillofacial surgery based on morphable models and neural networks: A preliminary assessment for anthropometry accuracy.

Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery
OBJECTIVES: This study aimed to evaluate the anthropometric accuracy of 3D face reconstruction based on neural networks (3DFRBN) using 2D images, including the assessment of global errors and landmarks, as well as linear and angular measurements.

A dual-stream model based on PRNU and quaternion RGB for detecting fake faces.

PloS one
The forensic examination of AIGC(Artificial Intelligence Generated Content) faces poses a contemporary challenge within the realm of color image forensics. A myriad of artificially generated faces by AIGC encompasses both global and local manipulatio...

Human-like face pareidolia emerges in deep neural networks optimized for face and object recognition.

PLoS computational biology
The human visual system possesses a remarkable ability to detect and process faces across diverse contexts, including the phenomenon of face pareidolia--seeing faces in inanimate objects. Despite extensive research, it remains unclear why the visual ...

Research of orthodontic soft tissue profile prediction based on conditional generative adversarial networks.

Journal of dentistry
OBJECTIVE: This study constructed a new conditional generative adversarial network (CGAN) model to predict changes in lateral appearance following orthodontic treatment.

Automatic Measurement of Frontomaxillary Facial Angle in Fetal Ultrasound Images Using Deep Learning.

Sensors (Basel, Switzerland)
Accurate measurement of frontomaxillary facial (FMF) angles in prenatal ultrasound (US) scans plays a pivotal role in the screening of trisomy 21. Nevertheless, this intricate procedure heavily relies on the proficiency of the ultrasonographer and te...