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Brain Tumor Classification using Pytroch and Tensorflow Transfer Learning Approach.

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Brain Tumor Classification

Dataset

Here I have used a publicly available dataset on Kaggle and used several classification algorithms to classify the tumor. There are 4 classes in the dataset:

  1. Glioma Tumor
  2. Meningioma Tumor
  3. Pituitary Tumor
  4. No Tumor

Frameworks

  • PyTorch

Models

I use the following models to classify Brain Tumor:

  • AlexNet
  • MobileNetV2
  • VGG16

Saved Models

I have saved the best performing model in the Saved Models folder.

Results

  • Single Inference has been done the separate notebook Inference.ipynb on the test_loader dataset which has not been used to train the models.
  • Inference outputs are saved in the Inference Images folder.
  • Training Results folder contains the training results of the models during training for example, training loss, validation loss, training accuracy, validation accuracy, etc.

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