Customized Skin Care Recommendations Using CNN Skin-Age Analysis
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Solution Overview
Problem
Consumers face difficulty in determining appropriate skin care products for their specific skin conditions, leading to ineffective treatments, as existing systems lack accurate analysis and product recommendation methods.
Innovation Solution
A convolutional neural network (CNN) based system analyzes facial images to predict skin age and identify contributing features, generating a heat map and recommending personalized skin care products or regimens using a trained CNN that reduces reliance on prior knowledge and enhances accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a convolutional neural network is used to analyze skin images, then measurement precision of skin age is improved, but device complexity increases
Solution Approach 1:
A trained convolutional neural network model serves as an intermediary between the input skin image and the skin age determination. The pre-trained CNN model processes the image analysis tasks, enabling accurate skin age measurement without requiring the end system to implement complex neural network architectures from scratch.
Solution Approach 2:
The convolutional neural network model is pre-trained on a large dataset of skin images with known ages before deployment. This preliminary training action enables the model to automatically learn and extract relevant skin features for age determination, eliminating the need for manual feature engineering and reducing the complexity of the deployment system.
2Ease of manufacture
If predetermined definitions and rules are used for skin analysis, then ease of manufacture is improved, but adaptability deteriorates
Solution Approach 1:
The patent replaces traditional mechanical rule-based skin analysis systems with a data-driven convolutional neural network approach. The CNN automatically learns skin analysis patterns from training data, substituting manual feature definition and rule-based decision making with automated feature extraction and classification, thereby improving adaptability while maintaining ease of deployment through pre-trained models.
Data Source
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AI summary
Systems and methods for providing customized skin care product recommendations. The system utilizes an image capture device and a computing device coupled to the image capture device. The computing device causes the system to analyze a captured image of a user via the by processing the image through a convolutional neural network to determine a skin age of the user. Determining the skin age may include identifying at least one pixel that is indicative of the skin age and utilizing the at least one pixel to create a heat map that identifies a region of the image that contributes to the skin age. The system may be used to determine a target skin age of the user, determine a skin care product for achieving the target skin age, and provide an option for the user to purchase the product.