We propose a deep learning approach for predicting the apparent age of a person's skin. Our method works by first normalizing a frontal image of a face and ...
We propose a deep learning approach for predicting the apparent age of a person's skin. Our method works by first normalizing a frontal image of a face and ...
This work proposes a deep learning approach for predicting the apparent age of a person's skin by first normalizing a frontal image of a face and cropping ...
Request PDF | On May 1, 2019, Matthew Shreve and others published Region-wise Modeling of Facial Skin Age using Deep CNNs | Find, read and cite all the ...
We propose a deep learning approach for predicting the apparent age of a person's skin. Our method works by first normalizing a frontal image of a face and ...
The proposed CNN architecture relies on a very deep face recognition CNN architecture which is capable of extracting facial features distinctively and robustly.
Missing: wise Skin
[176] proposed a classification system for facial skin diseases. They used three CNN models with transfer learning to classify five skin diseases of the face.
The main contribution of this paper is an extensive comparative analysis of several frameworks for real AAE based on deep learning architectures.
Recent studies on age estimation utilize convolutional neural networks (CNN), treating every facial region equally and disregarding potentially informative ...
Apr 18, 2021 · This study proposed a computerized process of classifying skin disease through deep learning based MobileNet V2 and Long Short Term Memory (LSTM).