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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM42607
Volume:
9 |
3 |
Mar 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
â Advancements in technology have significantly improved product recommendations, enhancing customer satisfaction and trust. Building upon this progress, the present paper explores a Deep Learning-based Skin Type and Skin Disease Analysis system designed to identify an individualâs skin condition and provide personalized recommendations for skincare and diet. This system employs state-of-the-art models, including Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), which are chosen for their scalability in terms of network width, depth and resolution. By integrating advanced deep learning techniques with image analysis, this project aims to provide users with reliable, data-driven insights into their skin health, fostering informed skincare and lifestyle choices.
KEYWORDS
Publication Date
3/19/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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