Product Name | Mirro skin analyzer, support English, French, German, Russian,
Spanish, Portuguese, Italian |
Function | skin analysis like acne, spot |
Package | 65*50*40cm, packed with box |
Product performance description
Through 28 million hd pixels to obtain facial skin image
conditions, using 8 spectral imaging technology,
AI face recognition technology, deep learning technology, 3D
simulation technology, cloud computing cloud storage, the
pathological features of the skin are quantitatively analyzed on
the surface and deep layer, and 14 skin health indicators can be
detected. Comprehensively analyze and evaluate skin problems, so as
to carry out scientific and accurate skin management with
reasonable basis .
Details Images
Semi-Automatic PET Bottle Blowing Machine Bottle Making Machine
Bottle Moulding Machine PET Bottle Making Machine is suitable for
producing PET plastic containers and bottles in all shapes.
The image is clearer and the analysis is more accurate RGB white
light, positive polarization, negative polarizationUV365, blue 405,
wu shi light, red light, brown lightComprehensive analysis of 14
skin indicators .
40 filters protect your skin from any side effects of light .
regularly upgrade version ,network interruption automatically
switches to the local end ,cloud computing and cloud storage .-
Product Usage
Product usage introduction
Description of product use effect
1. File management module
2. Cloud computing, cloud storage module
3. Surface and deep quantitative analysis module
4. Skin prediction module
5. 3D simulation module
6. Problem skin module
7. Comparative analysis module
8. Integrated report module
9. Solution module
10. VIP customized module
New 3D simulation technology:
Simulate accurate recognition of facial features, quantitative
analysis of four major
problematic skin.
Deep learning technology:
Combined with large database labeling, accurately identify and
analyze all kinds of skin problems.
AI face recognition technology:
Artificial intelligence face recognition algorithm is adopted to
accurately identify O area, T area and U area, making the data
more accurate and faster.
