| Type: | Skin Analyzer |
|---|---|
| Theory: | Skin Analyzer |
| Application: | Salon |
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Principle of this intelligent skin analyzer
Obtain facial skin image conditions through 28 million high-definition pixels, adopt 8-spectrum imaging technology, AI face recognition technology, deep learning technology, 3d simulation technology, cloud computing and cloud storage, and perform surface and deep quantitative analysis of the pathological characteristics of the skin. It can detect 14 skin health indicators. Comprehensive analysis and assessment of skin problems, so that scientific and accurate management of the skin can be carried out with reasonable evidence!
Ten modules of this intelligent skin analyzer
1. File management module
2. Cloud computing and cloud storage module
3. the surface and deep quantitative analysis module
4. the skin prediction module
5. problem skin module
6. 3d simulation module
7. comparative analysis module
8. comprehensive report module
9. solution module
10. VIP custom module
Hardware introduction
a. 2800w HD pixels: clearer images, more accurate identification, and more accurate analysis.
b. 8 spectrum imaging technology: rgb white light, positive polarization, negative polarization uv365, blue light 405, Wood's light, red light,14 skin indicators for brown skin analysis.
c. Wireless WiFi transmission upgrade version: Regularly upgrade the version, the network connection is automatically switched to the local end to solve the data upload. Disruption inconvenience issues, cloud computing, cloud storage items.
d. 40 filters: 40 filters are distributed beside the camera to ensure that the skin is not affected by any light
Software introduction
1. 3D simulation technology: 3D simulation accurately recognizes facial features and quantitatively analyzes four major problem skins
2. Deep learning technology: Combine with large database annotations to
accurately identify and analyze problems existing in various skins.
3. Ai face recognition technology: using artificial intelligence face recognition algorithm to accurately identify o area t area u area, Data is more accurate and faster.
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