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Found 2 papers, 1 papers with code
PositNN: Training Deep Neural Networks with Mixed Low-Precision Posit
Low-precision formats have proven to be an efficient way to reduce not only the memory footprint but also the hardware resources and power consumption of deep learning computations.
End-to-End Learning of Video Compression Using Spatio-Temporal Autoencoders
Deep learning (DL) is having a revolutionary impact in image processing, with DL-based approaches now holding the state of the art in many tasks, including image compression.
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