Technical Name An Intelligent Scalp Inspection and Diagnosis System
Project Operator Southern Taiwan University of Science and Technology
Project Host 張萬榮
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%.
Scientific Breakthrough
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.
Industrial Applicability
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.
Keyword Deep Learning Scalp Inspection System Artificial Intelligence (AI) Images Recognition Images Classification Internet of Things (IoT) Health Care AIoT Machine Learning Scalp Treatment
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