Advanced Skin Category Prediction System for Cosmetic Suggestion using Deep Convolution Neural Network

Nowadays, cosmetic products are quite important to a person’s look. Customers get access to a variety of products through online shopping and e-commerce websites. It is highly challenging to choose the ideal product for human skin. As such, this study proposed a novel system to accurately determine suitable product based on the skin type. The composition depends on skin types, which might be dry, oily, or normal. The composition proposal will be superior to the established method. This skin product selection process is made easier by utilizing deep learning techniques. The beauty sector is expanding rapidly over time, which has a positive knock-on effect on both the products it offers and its customers. The rapid growth of products and customers underscores the importance of choosing the right cosmetic product. There is a necessity to choose the ideal cosmetic product for oneself based on personal factors because cosmetics are important to one’s personality (i.e., skin type). As every person has a different skin texture, it might be challenging to find the right cosmetic for a customer’s skin type. Even if the right product for the consumer is selected, skin problems can still arise due to various complex issues. For solving this problem in the beauty industry, AI algorithms can be used as they provide better results when working with vast amounts of unstructured data.