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Customisation

Everyone’s skin is different, and different skin types require different skincare and haircare products. With the increasing demand for customised ingredients of personal care products, such as personalised perfumes, lipsticks and candles etc;

 

Feu keeps pace with the market change, providing customised skincare and haircare concept, allowing customers to add functional boosters at a reasonable price, create your own unique formula to achieve perfect youthful-looking skin.

 

The Theory of AI Skin Analysis Technology 

 

AI skin analysis technology is based on a combination of computer vision, machine learning, and image processing techniques. The goal of the technology is to analyse skin images and identify patterns and features that are associated with different skin conditions, such as acne, wrinkles, and dark spots. To achieve this, we use deep learning algorithms, which are a type of machine learning algorithm that are particularly effective at analysing visual data. Deep learning algorithms are composed of multiple layers of artificial neurons that work together to recognize patterns and features in the data. 

 

These deep learning algorithms are trained on large datasets of skin images, carefully labelled with information about the skin condition present in the image, such as the presence or absence of acne, the severity of wrinkles, or the size of dark spots. The algorithm uses this labelled data to learn to recognize patterns and features that are associated with these skin conditions. Once the algorithm has been trained, it can be used to analyse new images of skin and provide an assessment of the skin's condition. To do this, the algorithm breaks down the image into smaller parts, such as individual pixels or patches of skin. It then analyses each part of the image to identify patterns and features that are associated with specific skin conditions.

 

Finally, the algorithm combines all of the information it has gathered to provide an overall assessment of the skin's condition. This assessment might include information about the presence and severity of specific skin conditions, as well as recommendations for personalized skincare products or routines that could help improve the skin's health.

 

Overall, our skin analysis technology is a powerful tool for helping people understand their skin better and make more informed decisions about their skincare. By using deep learning algorithms and other advanced image processing techniques, we are able to provide accurate and personalised skin analysis that can help people achieve healthier, more radiant skin.

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AI人工智能皮膚分析技術之原理

AI人工智能皮膚分析技術結合了電腦視覺、機器學習和圖像處理技術。該技術目標是分析皮膚影像並識別不同皮膚狀況的模式和特徵,如粉刺、暗瘡、皺紋和黑斑等。要成功做到這點,此技術採用「深度學習算法」,這算法是一種非常強大的分析視覺數據機器學習算法,由多層人造神經元所組成,共同協作來識別數據中的皮膚模式和特徵。

 

這個深度學習算法是跟據大量的皮膚圖像訓練,圖像中呈現的皮膚狀況如粉刺、暗瘡、皺紋或黑斑、嚴重程度或大小,算法就可使用這些數據來識別與這些皮膚狀況相關聯的狀態和特徵。當算法訓練完成後,就可以用來分析新的皮膚影像並提供對皮膚情況的評估。要做到這一點,算法將影像分解成更小部分,如單個像素或小塊皮膚,然後分析影像中每一部分小塊以識別與特定皮膚問題的關聯性。

 

算法收集了所有資訊後會結合作一個整體皮膚評估。這個評估包括特定皮膚情況的問題和嚴重程度,以及針對個人化護膚產品的建議,可以幫助改善皮膚健康。

 

AI人工智能皮膚分析技術是一種非常強力的工具,可以幫助使用者更清楚了解自己的皮膚狀態並作出更明智的護膚選擇。通過使用深度學習算法和其他先進的影像處理技術,可以提供準確、快速和便捷的皮膚分析服務。

12種即時皮膚分析