---
license: mit
tags:
- medical
- cnn
- dermatology
- melanoma
---

# simpleNet: Skin Lesion Classification (Benign vs Malignant)

**simpleNet** is a lightweight Convolutional Neural Network (CNN) model for binary skin lesion classification, distinguishing between **benign** and **malignant (melanoma)** cases.  

## Model Description
- Architecture: Custom CNN with 3 convolutional blocks and regularization (Batch Normalization, Dropout, L2).  
- Input size: **224 × 224 × 3 RGB images**.  
- Output: 2 classes → `["benign", "malignant"]`.  
- Trained on a combination of curated skin lesion datasets, including **ISIC** samples.  

The model is optimized for **generalization** and has been validated with external images, showing robust performance for melanoma detection.

## Intended Use
- **Educational and research purposes**.  
- Demonstrating the potential of CNNs for medical imaging.  
- Not intended for clinical use without further validation and regulatory approval.