Age-based facial recognition using convoluted neural network deep learning algorithm

• Main Authors: Julius Yong Wu Jien, Aslina Baharum, Shaliza Hayati A. Wahab, Nordin Saad, Muhammad Omar, Noorsidi Aizuddin Mat Noor
• Format: Article
• Language: English; English
• Published: 2020
• Subjects: Q Science (General)
• Online Access: https://eprints.ums.edu.my/id/eprint/26251/1/Age-based%20facial%20recognition%20using%20convoluted%20neural%20network%20deep%20learning%20algorithm.pdf; https://eprints.ums.edu.my/id/eprint/26251/2/Age-based%20facial%20recognition%20using%20convoluted%20neural%20network%20deep%20learning%20algorithm1.pdf; https://eprints.ums.edu.my/id/eprint/26251/; https://doi.org/10.11591/ijai.v9.i3.pp424-428

Face recognition is the use of biometric innovations that can see or validate a person by seeing and investigating designs depending on the shape of the individual. Face recognition is used largely for the purpose of well-being, despite the fact that passion for different areas of use is growing. Overall, face recognition innovations are worth considering because they have the potential for broad legal jurisdiction and different business applications. It is widely used in many spaces. How it works is a product of facial recognition processing facial geometry. The hole between the ear and the good way from the front to the jaw are the main variables. This code distinguishes the highlight of the face that is important for your facial separation and creates your facial expression. Therefore, this study gives an overview of age detection using a different combination of machine learning and image processing methods on the image dataset.