In addition, Linear Discriminant Analysis (LDA) technique is applied for the facial component detection process. Primarily, the Bilateral Filtering (BF) technique is employed as an image pre-processing technique to boost the facial image quality. Therefore, this paper considers AGE as a multi-class classification issue and designs an Automated Deep Learning-based Age Group Estimation Model (ADL-AGEM) using facial images. Faces from distinct age groups have alike features making the facial AGE more difficult. The stochastic behavior of aging between individuals makes AGE depending upon facial images a tedious process. The AGE technique aims to classify the age group of the person using the facial image. Age Group Estimation (AGE) from frontal face images becomes useful in several application areas. At present times, there have been many studies on the automated extraction of facial information using machine learning.
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