NaviSplit introduces a dynamic multi-branch split DNN framework for UAV navigation that runs perception on-device and control on-edge, achieving 72-81% depth accuracy with 1.2-18 KB transmissions and 95% lower data rate than static alternatives.
Squeezenext: Hardware-aware neural network design,
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CADENCE dynamically adjusts a slimmable depth estimation network's computational load according to context, cutting energy expenditure by 75% and boosting navigation accuracy by 7.43% versus static baselines.
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NaviSplit: Dynamic Multi-Branch Split DNNs for Efficient Distributed Autonomous Navigation
NaviSplit introduces a dynamic multi-branch split DNN framework for UAV navigation that runs perception on-device and control on-edge, achieving 72-81% depth accuracy with 1.2-18 KB transmissions and 95% lower data rate than static alternatives.
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CADENCE: Context-Adaptive Depth Estimation for Navigation and Computational Efficiency
CADENCE dynamically adjusts a slimmable depth estimation network's computational load according to context, cutting energy expenditure by 75% and boosting navigation accuracy by 7.43% versus static baselines.