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English(EN) A Transfer Learning-Driven Methodology for Efficient and Sustainable Indoor Localization Using VLC

新的迁移学习方法提高了室内定位效率

研究人员开发了一种使用可见光通信(VLC)的室内定位新迁移学习方法。该方法旨在通过减少当前定位技术普遍存在的广泛数据收集和特定环境校准的需求来提高效率和可持续性。所提出的系统解决了照明变化和物理障碍等环境可变性问题,同时还降低了计算和能源需求。引入了一个新指标——模型效率(ME),以全面评估定位精度、能源效率、数据效率和迁移增益。 AI

影响 这种方法可能为工业应用带来更高效、可扩展的室内定位系统,从而降低能耗并在动态环境中提高精度。

排序理由 该集群描述了一篇详细介绍室内定位新方法的论文。

在 Hugging Face Daily Papers 阅读 →

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新的迁移学习方法提高了室内定位效率

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该集群描述了一篇详细介绍室内定位新方法的论文。
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报道来源 [2]

  1. arXiv cs.LG TIER_1 English(EN) · Masood Jan, Wafa Njima, Xun Zhang, Alexander Artemenko ·

    一种基于迁移学习的高效可持续可见光通信室内定位方法

    arXiv:2610.29594v1 Announce Type: new Abstract: The rapid expansion of the Internet of Things enables seamless collaboration among connected devices, making indoor localization a critical component of industrial automation. However, conventional localization techniques struggle i…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    一种基于迁移学习的高效可持续可见光通信室内定位方法

    The rapid expansion of the Internet of Things enables seamless collaboration among connected devices, making indoor localization a critical component of industrial automation. However, conventional localization techniques struggle in dynamic environments. These methods depend on …