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Histopathological Lung Cancer Classification
Deep learning project achieving ~99% accuracy in lung cancer classification using transfer learning with ResNet-50 and attention mechanisms (CBAM).
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The Problem
Accurate and automated classification of lung cancer from complex histopathological images.
How it Works
Implemented transfer learning with ResNet-50, fine-tuned with controlled freezing/unfreezing, explored CBAM attention mechanisms, and utilized GPU-accelerated training.
Future Improvements
- Optimize performance for real-time processing.
- Add support for multi-user collaboration.
- Integrate cloud storage for data persistence.
Tech Stack
PyTorchResNet-50Computer VisionTransfer LearningPandasMatplotlib
Links
No links available