SartajBhuvaji/Brain-Tumor-Classification-Using-Deep-Learning-Algorithms

To Detect and Classify Brain Tumors using CNN and ANN as an asset of Deep Learning and to examine the position of the tumor.

36
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Emerging

Implements comparative benchmarking across ANN, CNN, and transfer learning (VGG16) architectures on 3,260 augmented MRI images to classify tumors into three categories (benign, malignant, pituitary), achieving 94% validation accuracy with VGG16. Leverages T1-weighted contrast-enhanced MRI data and includes a web interface alongside the core classification models. Integrates with Kaggle datasets and HuggingFace for dataset distribution, with extensible contribution framework for community-submitted architectures.

No License No Package No Dependents
Maintenance 6 / 25
Adoption 9 / 25
Maturity 1 / 25
Community 20 / 25

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88

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31

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Last pushed

Nov 08, 2025

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