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English(EN) Detecting and measuring respiratory events in horses during exercise with a microphone: deep learning vs. standard signal processing

深度学习模型在检测马匹呼吸事件方面优于传统方法

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发并比较了深度学习模型与传统信号处理技术在检测和测量马匹运动时呼吸事件方面的性能。这项针对标准种快步马的研究发现，时间卷积网络（TCN）在准确估计呼吸频率方面优于长短期记忆（LSTM）网络和信号处理方法。TCN在检测呼气声音方面达到了0.94的中位数F1分数，即使在运动强度较低、声音不太明显的情况下也显示出有希望的结果。 AI

影响 这项研究展示了深度学习在动物健康监测方面的一个新应用，有望改善马匹福利和训练。

排序理由 这是一篇详细介绍深度学习模型在特定科学问题上的新应用的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

深度学习模型在检测马匹呼吸事件方面优于传统方法

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这是一篇详细介绍深度学习模型在特定科学问题上的新应用的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Jeanne I. M. Parmentier (Utrecht University, University of Twente, Inertia Technology B.V), Rhana M. Aarts (Utrecht University), Elin Hernlund (Swedish University of Agricultural Sciences), Marie Rhodin (Swedish University of Agricultural Sciences), Bere… ·

    使用麦克风检测和测量运动中马匹的呼吸事件：深度学习与标准信号处理的对比

    arXiv:2508.02349v2 Announce Type: replace-cross Abstract: Monitoring respiration parameters such as respiratory rate could be beneficial to understand the impact of training on equine health and performance and ultimately improve equine welfare. In this work, we compare deep lear…

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