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Assessment and Estimation of Face Detection Performance Based on Deep Learning for Forensic Applications.

Sensors (Basel, Switzerland)
Face recognition is a valuable forensic tool for criminal investigators since it certainly helps in identifying individuals in scenarios of criminal activity like fugitives or child sexual abuse. It is, however, a very challenging task as it must be ...

Sparse Spatiotemporal Descriptor for Micro-Expression Recognition Using Enhanced Local Cube Binary Pattern.

Sensors (Basel, Switzerland)
As a spontaneous facial expression, a micro-expression can reveal the psychological responses of human beings. Thus, micro-expression recognition can be widely studied and applied for its potentiality in clinical diagnosis, psychological research, an...

Identifying Facial Features and Predicting Patients of Acromegaly Using Three-Dimensional Imaging Techniques and Machine Learning.

Frontiers in endocrinology
Facial changes are common among nearly all acromegalic patients. As they develop slowly, patients often fail to notice such changes before they become obvious. Consequently, diagnosis and treatment are often delayed. So far, convenient and accurate ...

Age-Related Differences in Fixation Pattern on a Companion Robot.

Sensors (Basel, Switzerland)
Recent studies have addressed the various benefits of companion robots and expanded the research scope to their design. However, the viewpoints of older adults have not been deeply investigated. Therefore, this study aimed to examine the distinctive ...

Constructing an automatic diagnosis and severity-classification model for acromegaly using facial photographs by deep learning.

Journal of hematology & oncology
Due to acromegaly's insidious onset and slow progression, its diagnosis is usually delayed, thus causing severe complications and treatment difficulty. A convenient screening method is imperative. Based on our previous work, we herein developed a new...

Parallel ensemble learning of convolutional neural networks and local binary patterns for face recognition.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Face recognition success rate is influenced by illumination, expression, posture change, and other factors, which is due to the low generalization ability of a single convolutional neural network. A new face recognition meth...

Differentiating molecular etiologies of Angelman syndrome through facial phenotyping using deep learning.

American journal of medical genetics. Part A
Angelman syndrome (AS) is caused by several genetic mechanisms that impair the expression of maternally-inherited UBE3A through deletions, paternal uniparental disomy (UPD), UBE3A pathogenic variants, or imprinting defects. Current methods of differe...

A preliminary evaluation of still face images by deep learning: A potential screening test for childhood developmental disabilities.

Medical hypotheses
Most developmental disorders are defined by their clinical symptoms and many disorders share common features. The main objective of this research is to evaluate still facial images as a potential screening test for childhood developmental disabilitie...

Facial Expression Recognition Based on Weighted-Cluster Loss and Deep Transfer Learning Using a Highly Imbalanced Dataset.

Sensors (Basel, Switzerland)
Facial expression recognition (FER) is a challenging problem in the fields of pattern recognition and computer vision. The recent success of convolutional neural networks (CNNs) in object detection and object segmentation tasks has shown promise in b...

Deeply Learned Classifiers for Age and Gender Predictions of Unfiltered Faces.

TheScientificWorldJournal
Age and gender predictions of unfiltered faces classify unconstrained real-world facial images into predefined age and gender. Significant improvements have been made in this research area due to its usefulness in intelligent real-world applications....