We propose a deep learning based intelligent scalp inspection and diagnosis system for caring hair scalp health. The proposed system can automatically recognize the status of the user＇s scalp. As a result, we can get quantitative data on the scalp, including bacteria, allergies, dandruff, grease, and hair loss. Moreover, the experimental results showed that the accuracy can be achieved up to 90.909%.

To the best of our knowledge, there are no related automatically recognized products on the current markets in the world. We are the first applying deep learning based techniques to hair scalp inspection for the caring scalp health purpose. Moreover, the experimental results of our proposed system showed that the accuracy can be achieved up to 90.909% that is over human average accuracy.

The proposed system provides health automatic scalp image
recognition, which can significantly be reduced the cost of domestic hair salon service and enhance customer trust.