21.5 Inch Screen Moji Ai Skin Scanner Skin Analysis Machine for Digital Face Scan & Skin Health Evaluation

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 .

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 light Comprehensive 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 andcloud storage.

Advantage

1. 2800W High-Definition Pixel: Clearer image, more accurate recognition, more accurate analysis.

2. 8 Spectral Imaging Technology: RGB white light, positive polarization, negative polarization, UV365, wood's light blue light 405, red light, brown light comprehensive analysis of skin 14 skin indicators.

3. 40 Led Light Source Filters: 40 filters are distributed around the camera to protect the skin from any side effects of light.

4. Wireless WIFI Transmission Upgrade Version: Regular upgrade version, network connection interruption automatically switch to the local end, completely solve the problem of data upload interruption,  cloud computing, cloud storage.

5. Software New Upgrade Newest

6. 3D Simulation Technology: Simulate accurate recognition of facial features, quantitative analysis of four major problematic skin.

7. Deep Learning Technology: Combined with large database annotation, accurately identify and analyze various skin problems.

8. AI Face Recognition Technology: Artificial intelligence face recognition algorithm is adopted to accurately identify O area, T area and U area, making the datamore accurate and faster.

Technical Specification