Skin Type Analysis Application
Medical-grade classification using transfer learning
Overview
A medical imaging application that classifies skin types using deep learning and transfer learning techniques in MATLAB.
Problem Statement
Accurate skin type classification is essential for dermatological applications and personalized skincare recommendations, but manual assessment is time-consuming and subjective.
Technical Approach
Utilized EfficientNet-B0 as the base model with transfer learning to adapt pre-trained features for skin classification. Implemented in MATLAB's Deep Learning Toolbox for streamlined development and deployment.
Key Features
- EfficientNet-B0 transfer learning
- Multi-class skin type classification
- Image preprocessing pipeline
- Model evaluation metrics
- MATLAB-based deployment
Challenges & Learnings
Working with limited medical imaging data required careful data augmentation and transfer learning strategies to prevent overfitting while maintaining classification accuracy.
Outcome
Developed a functional skin type classifier achieving reliable accuracy on test datasets, demonstrating the viability of transfer learning for medical imaging tasks.