1. Model Capabilities:
Predicts skin conditions such as acne, eczema, psoriasis, and others with high confidence using
a trained Convolutional Neural Network (CNN). Supports both uploaded and webcam-captured images
for real-time analysis.
2. Diagnosis Insights:
Each prediction includes a confidence score to indicate the model’s certainty. Suggestions are
dynamically generated based on model output using OpenAI's GPT engine.
3. Live Deployment Features:
Automatically deletes uploaded images after 20 minutes to ensure user privacy. Supports both
light and dark themes for accessibility and user comfort.
4. User Interaction:
Users can preview, upload, and receive instant AI feedback on the web dashboard. Background
animations enhance visual engagement without affecting performance.
5. Tech Highlights:
Model trained using TensorFlow/Keras on labeled dermatology image data. Flask powers the backend
API, with jQuery/JS handling UI interactions. APScheduler cleans up stored data to prevent
storage bloat.
github
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Thanthai Periyar Govt Arts And Science College | Jun 2022 - Apr 2025
I have done here a lot of technical things with Data Science, Machine Learning, Deep Learning, Artificial Intelligence, and ERP Software. Project -2: Skin-Doctor Based on Image classification Project-1: Online-Dataset-Downloader
Soma Sundaram Chettiar Higher Sec School | Jun 2021 – Apr 2022
Group: Computer Maths
Board: State Board
Year : 2022
GR SoftTech | 2025 Jan - Running
Data analysis project with python, SQL, Python, And Excel Using various kinds of data sets to create various interactive dashboards, such as supply chain, Survey Data Analysis, Sales Analysis etc.
Digi plus | 2024 Aug - 2024 Nov
the content will be added feature
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