Real Time Detection of the Various Sign of Ageing Using Deep Learning
A. Krishna Sameera, V. Samuktha, Tafhimul Islam Akash, M. Sabeshnav, S. H. Krishna Veni · 2022
One of the most promising fields where the technology of deep learning and CNN can thrive are the cosmetic and dermatology industries. Detection of conditions like premature ageing can be made easy by deep learning procedures like facial detection and recognition. This project is based on improving the technology principally in these domains. A deep learning model utilizing CNNs is built, and the network is equipped with hand-crafted characteristics like wrinkles, acne and blemishes. The model will be able to distinguish these features concurrently and has diverse applications. It is computationally efficient compared to previous models, and it uses special convolution and pooling operations and performs parameter shifting. An overall accuracy of 94.11 % was achieved.