metadata
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.