Galaxy Morphology Classification
An interpretable deep learning project for classifying galaxy morphologies (Elliptical vs Spiral) using the Galaxy Zoo 2 dataset from SDSS images. Achieved 99.07% accuracy and ROC-AUC 0.9995 with ResNet18 transfer learning. Features Grad-CAM and Integrated Gradients for scientific interpretability.
Proof points
- 99.07% Accuracy
- ROC-AUC 0.9995
Technologies
PyTorch, ResNet18, Grad-CAM, Captum, Astropy, NumPy