Intelligent Skincare: AI-Driven Cosmetic Product Recommendation Using Advanced Machine Learning Models
DOI:
https://doi.org/10.47672/ajhmn.2621Abstract
Purpose: This research presents an advanced AI-powered system designed to revolutionize cosmetic product selection by providing highly personalized recommendations based on individual skin characteristics.
Materials and Methods: Unlike traditional methods relying on beauty consultants or algorithm-based digital platforms, the proposed system leverages deep learning models to enhance precision, efficiency, and reliability.
Findings: At its core, the system employs state-of-the-art image recognition models, including Convolutional Neural Networks (CNN) with 92% accuracy, VGGNet at 94%, and DenseNet achieving 98%, to analyze user-uploaded skin images and identify dermatological concerns such as dryness, oiliness, and red spots. By integrating sophisticated AI methodologies, the system generates scientifically informed recommendations across skincare, makeup, and haircare categories.
Implications to Theory, Practice and Policy: This study bridges the gap between AI and personalized skincare, offering an innovative, data-driven approach that enhances the consumer experience with evidence-based, highly tailored cosmetic guidance. Through AI-driven dermatological analysis, this research contributes to the advancement of intelligent skincare solutions, ensuring precise, effective, and scientifically backed product recommendations.
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A. Kothari, D. Shah, T. Soni and S. Dhage, "Cosmetic Skin Type Classification Using CNN With Product Recommendation," 2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT), Kharagpur, India, 2021, pp. 1-6, doi: 10.1109/ICCCNT51525.2021.9580174.
H. Singh, P. Agarwal, and L. Qi, "Skinwise MR:novel approach for natural beauty remedy recommendation system using machine learning," in Proc. IEEE Int. Conf. Data Sci. Adv. Anal., 2023,
Nguyen, A. T. P., Shak, M. S., & Al-Imran, M. (2024). ADVANCING EARLY SKIN CANCER DETECTION: A COMPARATIVE ANALYSIS OF MACHINE LEARNING ALGORITHMS FOR MELANOMA DIAGNOSIS USING DERMOSCOPIC IMAGES. International Journal of Medical Science and Public Health Research, 5(12), 119-133.
P. R. H. Perera, E. S. S. Soysa, H. R. S. De Silva, A. R. P. Tavarayan, M. P. Gamage and K. M. L.
P. Vatiwutipong, S. Vachmanus, T. Noraset and S. Tuarob, "Artificial Intelligence in Cosmetic Dermatology: A Systematic Literature Review," in IEEE Access, vol. 11, pp. 71407-71425, 2023, doi:
P. Weerasinghe, "Virtual Makeover and Makeup Recommendation Based on Personal Trait Analysis," 2021 InternationalConference on Advancements in Computing, Colombo, Sri Lanka,2021,pp.288293,doi:10.1109/ICAC54203.2021.96
Phan, H. T. N. (2024). EARLY DETECTION OF ORAL DISEASES USING MACHINE LEARNING: A COMPARATIVE STUDY OF PREDICTIVE MODELS AND DIAGNOSTIC ACCURACY. International Journal of Medical Science and Public Health Research, 5(12), 107-118.
pp. 789-795, doi: 10.1109/DSAA.2023.00095.
R. S, H. S, K. Jayasakthi, S. D. A, K. Latha and N. Gopinath, "Cosmetic Product Selection Using Machine Learning," 2022 International Conference on Communication, Computing and Internet of Things (IC3IoT), Chennai, India, 2022, pp. 1-6, doi: 10.1109/IC3IOT53935.2022.9767972
R. S, H. S, K. Jayasakthi, S. D. A, K. Latha and N. Gopinath, "Cosmetic Product Selection Using Machine Learning," 2022 Computing and Internet of Things (IC3IoT), Chennai, India, 2022, pp. 1-6, doi: 10.1109/IC3IOT53935.2022.9767972
S. Bhuvana, B. G. S, S. S. M and S. J. V, "Cosmetic Suggestion System Using Convolution Neural Network," 2022 3rd International Conference on Electronics and Sustainable Communication Systems (ICESC), Coimbatore, India, 2022, pp. 1084-1089, doi: 10.1109/ICESC54411.2022.9885369.
S. Ray, A. M, A. K. Rao, S. K. Shukla, S. Gupta and P. Rawat, "Cosmetics Suggestion System using Deep Learning," 2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS), Tashkent, Uzbekistan, 2022, pp. 680-684, doi: 10.1109/ICTACS56270.2022.9987850.
Shin,Haeran Lim,Yujung "Design and Implementation of a Cosmetics Recommendation System Based on Machine Learning in Social media Environments" IEEE Trans. Pattern Anal. Mach. Intell., vol. 45, no. 7, pp. 3175-3183, Jul. 2023, doi: 10.1109/TPAMI.2023.3056741.
Y. Nakajima, H. Honma, H. Aoshima, T. Akiba and S.Masuyama, "Recommender System Based on User Evaluations and Cosmetic Ingredients," 2019 4th International Conference on Information Technology (InCIT), Bangkok, Thailand, 2019, pp. 22-27, doi: 10.1109/INCIT.2019.8912051.
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