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Lossy Medical Image Compression using Residual Learning-based Dual Autoencoder Model
In this work, we propose a two-stage autoencoder based compressor-decompressor framework for compressing malaria RBC cell image patches.
Deep learning-based Edge-aware pre and post-processing methods for JPEG compressed images
We propose a learning-based compression scheme that envelopes a standard codec between pre and post-processing deep CNNs.
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