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The “Skin Care Analysis System using Deep Learning” is an innovative project aimed at revolutionizing personalized skincare diagnostics and recommendations. This web-based system employs a robust deep learning model, constructed with Keras and Convolutional Neural Networks (CNN), capable of accurately classifying 9 different skin diseases. Users are engaged through an intuitive web interface featuring user authentication, a survey module, and image upload capabilities. The system analyzes uploaded facial images, providing real-time predictions for skin conditions such as acne, melanoma, Eczema, and more. Additionally, a novel bruise detection feature enhances the system’s utility, enabling users to identify various types of skin discolorations. Benefits include early disease detection, personalized skincare recommendations, and user empowerment through insights into skin health. The system aims to reduce healthcare costs, promote skin health awareness, and provide a convenient, accessible, and data-driven platform for skincare analysis. Future enhancements, such as skin evolution analysis and foundation match recommendations, further position the project at the forefront of technology-driven skincare solutions. This project signifies a significant advancement in the intersection of technology and healthcare, offering users a comprehensive and user-friendly approach to personalized skincare.

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Implementation of Skin Disease Identification and Analysis Through Deep Learning

  • 章节

  • 发表日期：

    2025年

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  • Debasree Mitra,
  • Antara Das,
  • Aradhya Rai,
  • Ritoja Banerjee,
  • Kanhaiya Kumar

摘要

The “Skin Care Analysis System using Deep Learning” is an innovative project aimed at revolutionizing personalized skincare diagnostics and recommendations. This web-based system employs a robust deep learning model, constructed with Keras and Convolutional Neural Networks (CNN), capable of accurately classifying 9 different skin diseases. Users are engaged through an intuitive web interface featuring user authentication, a survey module, and image upload capabilities. The system analyzes uploaded facial images, providing real-time predictions for skin conditions such as acne, melanoma, Eczema, and more. Additionally, a novel bruise detection feature enhances the system’s utility, enabling users to identify various types of skin discolorations. Benefits include early disease detection, personalized skincare recommendations, and user empowerment through insights into skin health. The system aims to reduce healthcare costs, promote skin health awareness, and provide a convenient, accessible, and data-driven platform for skincare analysis. Future enhancements, such as skin evolution analysis and foundation match recommendations, further position the project at the forefront of technology-driven skincare solutions. This project signifies a significant advancement in the intersection of technology and healthcare, offering users a comprehensive and user-friendly approach to personalized skincare.