Brain Tumor Classification

This project focuses on brain tumor classification using various Convolutional Neural Network (CNN) architectures, including VGG16, VGG19, ResNet50, InceptionV3, Xception, InceptionResNetV2, MobileNet, DenseNet, NASNet, MobileNetV2, EfficientNet, and ResNet152V2. The dataset used consists of brain MRI images, which are employed for detecting brain tumors.

The project explores the application of these CNN models for accurate classification and analysis of brain tumor images, comparing their performance and effectiveness in detecting tumors. It serves as an in-depth study of different deep learning models for medical image classification tasks.