AIMC Topic: Face

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Application of deep learning artificial intelligence technique to the classification of clinical orthodontic photos.

BMC oral health
BACKGROUND: Taking facial and intraoral clinical photos is one of the essential parts of orthodontic diagnosis and treatment planning. Among the diagnostic procedures, classification of the shuffled clinical photos with their orientations will be the...

Face Sketch Synthesis Using Regularized Broad Learning System.

IEEE transactions on neural networks and learning systems
There are two main categories of face sketch synthesis: data- and model-driven. The data-driven method synthesizes sketches from training photograph-sketch patches at the cost of detail loss. The model-driven method can preserve more details, but the...

Analysis of facial ultrasonography images based on deep learning.

Scientific reports
Transfer learning using a pre-trained model with the ImageNet database is frequently used when obtaining large datasets in the medical imaging field is challenging. We tried to estimate the value of deep learning for facial US images by assessing the...

Initial validation of a new device for facial skin analysis.

The Journal of dermatological treatment
The field of dermatology is met with many subjective analysis methods. Due to the relative nature of subjective analysis methods, objective analysis methods with greater accuracy and reliability were developed. Many of these devices are either inacce...

A digital mask to safeguard patient privacy.

Nature medicine
The storage of facial images in medical records poses privacy risks due to the sensitive nature of the personal biometric information that can be extracted from such images. To minimize these risks, we developed a new technology, called the digital m...

Accuracy and clinical relevance of an automated, algorithm-based analysis of facial signs from selfie images of women in the United States of various ages, ancestries and phototypes: A cross-sectional observational study.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: Real-life validation is necessary to ensure our artificial intelligence (AI) skin diagnostic tool is inclusive across a diverse and representative US population of various ages, ancestries and skin phototypes.

Acne Detection by Ensemble Neural Networks.

Sensors (Basel, Switzerland)
Acne detection, utilizing prior knowledge to diagnose acne severity, number or position through facial images, plays a very important role in medical diagnoses and treatment for patients with skin problems. Recently, deep learning algorithms were int...

Classification of facial paralysis based on machine learning techniques.

Biomedical engineering online
Facial paralysis (FP) is an inability to move facial muscles voluntarily, affecting daily activities. There is a need for quantitative assessment and severity level classification of FP to evaluate the condition. None of the available tools are widel...

Fast-GANFIT: Generative Adversarial Network for High Fidelity 3D Face Reconstruction.

IEEE transactions on pattern analysis and machine intelligence
A lot of work has been done towards reconstructing the 3D facial structure from single images by capitalizing on the power of deep convolutional neural networks (DCNNs). In the recent works, the texture features either correspond to components of a l...

Regularization on Augmented Data to Diversify Sparse Representation for Robust Image Classification.

IEEE transactions on cybernetics
Image classification is a fundamental component in modern computer vision systems, where sparse representation-based classification has drawn a lot of attention due to its robustness. However, on the optimization of sparse learning systems, regulariz...