The phrase "aging features" is correct and usable in written English.
It can be used to describe physical characteristics or traits that indicate the passage of time, often in relation to a person's appearance or an object's condition.
Example: "The painting displayed aging features, with cracks and faded colors that told the story of its long history."
Alternatives: "signs of aging" or "age-related characteristics".
The facial skin aging features are extracted by using Local Gabor Binary Pattern Histogram (LGBPH) and wrinkle analysis.
Specifically, we use a convolutional neural network which can learn discriminative aging features from raw face images without any handcrafting.
Its main difficulty lies in how to design aging features that remain discriminative in spite of large facial appearance variations.
In order to learn more effective aging features, we further propose a comparative ranking layer which is supervised by a pair-wise comparative signal.
In this paper a novel method based on facial skin aging features and Artificial Neural Network (ANN) is proposed to classify the human face images into four age groups.
A chemical screen was later performed on these WRN-deficient MSCs, and interestingly, Vitamin C was found to be able to rescue many of the aging features, suggesting it be a potential treatment to alleviate Werner syndrome (Li et al., 2016).
There was no significant correlation for any of the hair aging features with the skin aging features or the perceived age data generated from the facial images.
However, hair aging features could be important modulators of age perception.
Additionally, it is unclear how the use of different photographic images in each study affects the relationship between perceived age and skin and hair aging features.
Here, to investigate the link between perceived age and biological age we have investigated the strength of relationship between how old women look for their age and skin, hair and lip aging features.
Furthermore, we have quantified the influence of genetic factors on skin, hair and facial aging features and found evidence that subcutaneous tissue plays a role in how old women look for their age.
