https://github.com/madhu102938/brain-tumor-classify
Brain Tumor Classification with various models
https://github.com/madhu102938/brain-tumor-classify
cnn explainable-ai resnet-101 resnet-50 tensorflow2 vgg19
Last synced: 7 months ago
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Brain Tumor Classification with various models
- Host: GitHub
- URL: https://github.com/madhu102938/brain-tumor-classify
- Owner: madhu102938
- Created: 2024-07-06T16:59:41.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-07-06T18:05:23.000Z (over 1 year ago)
- Last Synced: 2025-01-15T07:57:01.435Z (9 months ago)
- Topics: cnn, explainable-ai, resnet-101, resnet-50, tensorflow2, vgg19
- Language: Jupyter Notebook
- Homepage:
- Size: 5.94 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# brain-tumor-classify
[Dataset used](https://www.kaggle.com/datasets/masoudnickparvar/brain-tumor-mri-dataset/data)
Check `Brain Tumor MRI.pdf` for a detailed report
- `model1.ipynb` is the code for the custom model implemention
- `vgg19.ipynb` is the code for feature extraction of VGG19 model for the task, **ImageNet** weights were used
- `resnet50_scratch_ipynb` is the code for resnet50 implementation from scratch in tensorflow
- `resnet_101_freeze.ipynb` is the code for feature extraction of resnet101 model. **ImageNet** weights were used
- `resnet_101_allTrain.ipynb` is the code for finetuning of resnet101 model. **ImageNet** weights were used
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- `model1_shap.ipynb` is implementation of shaply explainable deep learning on custom implemention
- `layer_by_model1.ipynb` is implementation of layer-by-propagation for custom model
- layer-by-propagation is a technique by which we extract the output of intermediate layers to explain the output of the model