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    <title>射频传感 on 办公AI智能小助手</title>
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      <title>射频传感可解释性突破：复数值白盒Transformer</title>
      <link>https://blog.qife122.com/p/%E5%B0%84%E9%A2%91%E4%BC%A0%E6%84%9F%E5%8F%AF%E8%A7%A3%E9%87%8A%E6%80%A7%E7%AA%81%E7%A0%B4%E5%A4%8D%E6%95%B0%E5%80%BC%E7%99%BD%E7%9B%92transformer/</link>
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      <description>&lt;h1 id=&#34;射频传感可解释性突破复数值白盒transformer&#34;&gt;射频传感可解释性突破：复数值白盒Transformer&lt;/h1&gt;&#xA;&lt;p&gt;深度学习在射频（RF）领域的应用推动了深度无线传感（DWS）的重大进展。然而，现有DWS模型大多作为黑盒存在可解释性限制，这阻碍了其泛化能力并在安全敏感的物理应用中引发担忧。&lt;/p&gt;</description>
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