Facial wrinkle categorization using Convolutional Neural Network
A tool for the detection and classification of wrinkles on the facial skin is always welcomed in the pursuit of tight and beautiful skin. If this tool involves the use of a state-of-the-art neural network and high-quality images, there is a high likelihood that it will be practical. Five thousand an...
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PAGEPress Publications,
2024-09-01T00:00:00Z.
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LEADER | 00000 am a22000003u 4500 | ||
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001 | doaj_9a88ef7c91294ec6bbb8f401966718a4 | ||
042 | |a dc | ||
100 | 1 | 0 | |a Čedomir Vasić |e author |
245 | 0 | 0 | |a Facial wrinkle categorization using Convolutional Neural Network |
260 | |b PAGEPress Publications, |c 2024-09-01T00:00:00Z. | ||
500 | |a 10.4081/dr.2024.10034 | ||
500 | |a 2036-7392 | ||
500 | |a 2036-7406 | ||
520 | |a A tool for the detection and classification of wrinkles on the facial skin is always welcomed in the pursuit of tight and beautiful skin. If this tool involves the use of a state-of-the-art neural network and high-quality images, there is a high likelihood that it will be practical. Five thousand and ninety-eight images were categorized into four classes by a trained expert and prepared for neural network training. The task was to determine whether such prepared data could serve as good material for learning and whether they could provide sufficiently high accuracy in prediction. It was found that the answer to this question is positive. | ||
546 | |a EN | ||
690 | |a Classification | ||
690 | |a categorization | ||
690 | |a skin | ||
690 | |a wrinkle | ||
690 | |a CNN | ||
690 | |a Dermatology | ||
690 | |a RL1-803 | ||
655 | 7 | |a article |2 local | |
786 | 0 | |n Dermatology Reports (2024) | |
787 | 0 | |n https://www.pagepress.org/journals/dr/article/view/10034 | |
787 | 0 | |n https://doaj.org/toc/2036-7392 | |
787 | 0 | |n https://doaj.org/toc/2036-7406 | |
856 | 4 | 1 | |u https://doaj.org/article/9a88ef7c91294ec6bbb8f401966718a4 |z Connect to this object online. |