This projet aims to build a CNN based model which can accurately detect melanoma which is a type of cancer that accounts for 75% of skin cancer deaths if not detected early. A solution that can evaluate images and alert dermatologists about the presence of melanoma has the potential to reduce a lot of manual effort needed in diagnosis.
- TensorFlow
- Keras
- Python
The data set contains the following diseases:
- Actinic keratosis
- Basal cell carcinoma
- Dermatofibroma
- Melanoma
- Nevus
- Pigmented benign keratosis
- Seborrheic keratosis
- Squamous cell carcinoma
- Vascular lesion
- We started with a base CNN model with 3 convolution layers plus pooling layers followed by flattenning and two dense layers and later added dropout and augmented the data.
- The final model that best fit the data was obtained by rebalancing the data using Augmentor module