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Mar 12, 2024 · MSIN is designed to be computationally lightweight, minimizing the demand for computational resources during training. It can be trained ...
Mar 12, 2024 · In this paper, we propose a robust model to mitigate the problem of jitters and drifts in trajectory prediction by exploiting the spatial dependence in ...
Apr 15, 2024 · In particular, we design a framework (MSIN) to fuse the local spatial dependence of multiple sensors and incorporate the local spatial and ...
MSIN: An Efficient Multi-head Self-attention Framework for Inertial Navigation. https://doi.org/10.1007/978-981-97-0834-5_26 ·.
Article "MSIN: An Efficient Multi-head Self-attention Framework for Inertial Navigation" Detailed information of the J-GLOBAL is an information service ...
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Mar 23, 2024 · In this paper, we introduce TinyOdom, a framework for training and deploying neural inertial models on URC hardware. ... Self-Navigating Cars ...
Sep 17, 2022 · Hydra Attention is computationally linear in both tokens and features with no hidden constants, making it significantly faster than standard self-attention.
Missing: Inertial | Show results with:Inertial
Dec 3, 2021 · In this paper, we propose a novel robust Contextual Transformer-based network for Inertial Navigation~(CTIN) to accurately predict velocity and trajectory.
Missing: MSIN: | Show results with:MSIN:
Jun 28, 2022 · In this paper, we propose a novel robust Contextual Transformer-based net- work for Inertial Navigation (CTIN) to accurately predict ve- locity ...
Missing: MSIN: | Show results with:MSIN:
In this paper, we introduce TinyOdom, a framework for training and deploying neural inertial models on URC hardware.
Missing: MSIN: | Show results with:MSIN: