- Developed and trained a 3-layer SRCNN in PyTorch on 800+ high-res images (DIV2K), achieving strong PSNR/SSIM scores.
- Compared model performance across 2×, 3×, and 4× scaling factors using MLflow with 50+ experiment runs.
- Managed training infrastructure on AWS SageMaker with S3-backed data pipelines for 20GB+ of training data.
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Single Image Super Resolution (SRCNN)