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Spiking MoveNet architecture shows promise for satellite pose estimation

By PulseAugur Editorial · [2 sources] ·

Researchers have evaluated a spiking version of the MoveNet architecture, named S-MoveNet-Lightning, for pose estimation in autonomous spacecraft. This spiking neural network (SNN) approach aims to leverage energy efficiency and event-driven processing for embedded space applications. The study found that S-MoveNet-Lightning requires, on average, 2.2 times fewer multiplication and accumulation operations compared to the standard MoveNet-Lightning when deployed on FPGA platforms with AMD Deep Learning Processor Units. AI

IMPACT This research could pave the way for more energy-efficient AI deployments in resource-constrained environments like spacecraft.

RANK_REASON The cluster contains an academic paper detailing a new approach to pose estimation using spiking neural networks for satellite applications.

Read on arXiv cs.NE (Neural & Evolutionary) →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Spiking MoveNet architecture shows promise for satellite pose estimation

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The cluster contains an academic paper detailing a new approach to pose estimation using spiking neural networks for satellite applications.
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COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Jonathan Courtois, Christophe Marabotto, Benoit Miramond, Alain Pegatoquet ·

    Evaluating Spiking MoveNet Deployability for Near-Future Onboard Spiking Satellite Pose Estimation

    arXiv:2610.33061v1 Announce Type: cross Abstract: SNNs are attracting interest due to their potential for energy efficiency and event-driven processing. However, neuromorphic hardware is not yet mature enough to enable embedded deployment of complex spiking network architectures.…

  2. arXiv cs.NE (Neural & Evolutionary) TIER_1 English(EN) · Alain Pegatoquet ·

    Evaluating Spiking MoveNet Deployability for Near-Future Onboard Spiking Satellite Pose Estimation

    SNNs are attracting interest due to their potential for energy efficiency and event-driven processing. However, neuromorphic hardware is not yet mature enough to enable embedded deployment of complex spiking network architectures. In this work, we investigate a spiking version of…

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