CancerNet is an advanced deep learning project dedicated to precise cancer classification leveraging GoogleNet architecture implemented in Python using TensorFlow and Keras. This project achieves a remarkable 98% accuracy in classifying brain, kidney, lung and colon cancers. It involves meticulous hyperparameter tuning, integration of advanced CNN techniques, and the application of batch normalization for enhanced classification accuracy. Dataset Structure:
- Brain Cancer - Brain tumor, Brain menin
- kidney Cancer- kidney normal, kidney tumor
- lung cancer- lung aca(lung Adenocarcinoma) , lung bnt(lung benign tissue)
- colon cancer - colon aca(colon Adenocarcinoma) , colon bnt(colon benign tissue) DATASET LINK:https://www.kaggle.com/datasets/obulisainaren/multi-cancer