Name
Abstract | ||
|---|---|---|
This paper proposes a mobile device-based hairy scalp diagnosis system, which adopts deep learning techniques. The proposed system is composed of a mobile device, a cloud-based AI training server, and a cloud-based database. Moreover, the proposed system can detect and diagnose four common hairy scalp symptoms: dandruff, folliculitis, hair loss, and oily hair. As a result, the experimental results showed that the recognition accuracy of the proposed system could achieve up to 95.59%. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/LifeTech48969.2020.1570617332 | 2020 IEEE 2nd Global Conference on Life Sciences and Technologies (LifeTech) |
Keywords | DocType | ISBN |
Artificial intelligence over the Internet of Things (AIoT),deep learning,hairy scalp diagnosis,haircare,healthcare | Conference | 978-1-7281-7064-0 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wan-Jung Chang | 1 | 13 | 12.53 |
| Ming-Che Chen | 2 | 0 | 0.34 |
| Liang-Bi Chen | 3 | 26 | 18.40 |
| Yi-Chan Chiu | 4 | 0 | 0.34 |
| Chia-Hao Hsu | 5 | 44 | 11.63 |
| Yang-Kun Ou | 6 | 0 | 0.68 |
| Qiu Chen | 7 | 0 | 0.34 |