Release date: 2017-12-26
Recently, Meitu's AI technology research center, Meitu Imaging Laboratory MTlab, released its latest artificial intelligence technology: AI skin measurement technology MTskin, which diagnoses skin problems through a facial photo.
Founded in 2010, MTlab currently focuses on face technology, 3D vision, image recognition, AR technology, portrait beautification and image quality enhancement. Today there are 9 core technologies, including face technology, image stylization, image restoration, 3D technology, image segmentation, extreme beauty, image synthesis, beauty technology and AI skin measurement.
The AI ​​skin test released this time can take a self-portrait on a mobile phone to fully understand your skin condition. Support for Meitu AI skin measurement technology includes medical-grade image data, professional dermatologists for data marking, and more. According to reports, at present, in the five areas of skin quality, skin age, skin color, blackheads, dark circles, acne, the accuracy of AI recognition can be as high as 95%. Based on deep learning, Mito AI Smart Skin Measurement can even predict user skin trends in the future.
Xu Qingquan, technical director of Meitu Imaging Laboratory, said that a high-value beauty is a bunch of "0101" codes in the eyes of the computer. In the eyes of MTlab, I want to turn this "0101" code into a human being. The abstract information that is understood is analysis, the position of the face in the picture can be found, and the facial features of the user can be found; the 3D technology can reconstruct the real 3D model of the user; the image segmentation technology can segment the user's skin, facial features or even Hair, with this information, can be further processed.
“First we will input the user's skin image into the convolutional neural network. The convolutional neural network will recognize the picture entered by the user. Is there any flaw in her face? And what is the location of the ?? Finally, I will get a picture. The image of the cockroach is marked with all the 瑕疵 positions on the user's skin. With this image we can cut all the squats, we can input these shards into another neural network - to distinguish these 瑕疵What is the type?"
He said that the principle of AI skin measurement is to ask the authoritative doctor to coordinate the same data and count the results of multiple doctors. In terms of algorithm, taking ç‘•ç–µ detection as an example, it is divided into two steps, the first is the detection of the problem location, and the second is the classification of the type.
Source: AI Nuggets (Micro Signal HealthAI)
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