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neural-compression

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Neural-Compression-with-Autoencoders

Exploring advanced autoencoder architectures for efficient data compression on EMNIST dataset, focusing on high-fidelity image reconstruction with minimal information loss. This project tests various encoder-decoder configurations to optimize performance metrics like MSE, SSIM, and PSNR, aiming to achieve near-lossless data compression.

  • Updated Jun 1, 2024
  • Jupyter Notebook

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