Skin Disease Classification Using EfficientNet-B0

Developed a deep learning-based image classification system to classify skin images into 8 disease categories using the EfficientNet-B0 architecture.

Key Contributions:

- Implemented image preprocessing and preparation.

- Built and trained a classification model using PyTorch.

- Used OpenCV for image processing.

- Implemented model evaluation and inference.

- Achieved approximately 79% classification accuracy, as reported in the project CV.

This project demonstrates practical experience in medical image classification and deep learning.