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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Issue: April 2026
Volume 11 | Issue 4
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 119
Article Submitted : 23355
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Total Authors : 23952
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| Paper Title: | AI-Powered Personalized Skincare System |
| Authors Name: | B. Sai Anjanna Reddy , M. Parthu , C. Yogitha , Dr. Naadem Divya |
| Download E-Certificate: | Download |
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IJRTI_211603
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| Published Paper Id: | IJRTI2604170 |
| Published In: | Volume 11 Issue 4, April-2026 |
| DOI: | |
| Abstract: | One way this tool works is by letting people share pictures of their faces so it can check skin issues automatically. Built around a smart design, the interface stays clear and simple to move through. A special kind of math model, shaped like layers, studies each photo closely - this model was made with Keras, focusing on spotting patterns in pixels. Instead of treating every image differently, adjustments happen first: scaling down, balancing colors, smoothing contrasts - all steps that help accuracy later. Once ready, photos get sorted into groups like pimples, clogged holes, shadowy patches, open pores, or fine lines across the face. What comes next depends entirely on what shows up; suggestions appear based on findings. These include cleansers matched to needs, creams for hydration, sun protection choices, plus concentrated liquids targeting specific concerns. Not only does advice show up - it connects directly to places where those exact things can be bought online. Clicking takes someone straight there without extra searching needed. Each piece fits together quietly behind one screen. Starting off, the platform uses a chatbot to boost engagement, offering custom skincare tips based on real-time weather data. Built with Django, it ties together the visual part of the app, behind-the-scenes logic, and its analysis engine without hiccups. Security comes into play through reliable login systems, keeping personal details protected. At the end of each session, users receive a PDF file listing their identified skin issues paired with suggested care steps. To check how well the system works, common measures like accuracy, precision, recall, plus F1-score are used, along with a confusion matrix to dig into specific outcomes. It turns out the CNN-driven approach sorts skin issues reliably and quickly. Automated image scanning pairs with tailored advice, online shopping links, and responsive assistance, creating a path that's easier on the wallet than typical dermatology visits. This setup supports smarter personal choices about skin care without stepping into a clinic. |
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| Cite Article: | "AI-Powered Personalized Skincare System", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 4, page no.b240-b248, April-2026, Available :http://www.ijrti.org/papers/IJRTI2604170.pdf |
| Downloads: | 00031 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2604170
Registration ID:211603
Published In: Volume 11 Issue 4, April-2026
DOI (Digital Object Identifier):
Page No: b240-b248 Country: Medchal-Malkajgiri, Telangana, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2604170 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2604170 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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