FAJSCC is a new deepJSCC architecture for images that achieves better transmission performance with lower complexity than prior models and enables independent encoder-decoder compute adjustment.
Bjøntegaard delta (bd): A tutorial overview of the metric, evolution, challenges, and recommendations
2 Pith papers cite this work. Polarity classification is still indexing.
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Blackwell NVENC UHQ achieves up to 22.79% BD-Rate improvement over prior modes but raises end-to-end latency over 400% and board power by 40%, limiting it to VoD transcoding rather than interactive use.
citing papers explorer
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Feature Importance-Aware Deep Joint Source-Channel Coding for Computationally Efficient and Adjustable Image Transmission
FAJSCC is a new deepJSCC architecture for images that achieves better transmission performance with lower complexity than prior models and enables independent encoder-decoder compute adjustment.
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Evolution of NVENC Efficiency: A Longitudinal Analysis of HQ and UHQ Tuning Efficiency, Latency and Energy Trade-offs
Blackwell NVENC UHQ achieves up to 22.79% BD-Rate improvement over prior modes but raises end-to-end latency over 400% and board power by 40%, limiting it to VoD transcoding rather than interactive use.