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An Intelligent Scalp Inspection and Diagnosis System for Caring Hairy Scalp Health

This paper proposes an intelligent scalp inspection and diagnosis system based on the deep learning techniques for caring hair scalp health. The proposed system can automatically recognize the status of the user's scalp. Moreover, we can continuously increase in the number of samples to enhance the accuracy rate by adopting deep learning techniques. The proposed system consists of a scalp detector, an app running on a tablet, and a cloud management platform. The scalp detector will be connected with the tablet via Wi-Fi wireless network. Thus, a scalp photo can be captured via the proposed scalp detector. The scalp photo will be recognized by scalp detector, and the recognized result of the scalp will also be sent and displayed to the tablet. As a result, we can get the quantitative data on the scalp, including bacteria, allergies, dandruff, grease, and hair loss. Moreover. The experimental results showed that the accuracy can be achieved 90.909%.