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    <title>PyPI recent updates for napari-kld</title>
    <link>https://pypi.org/project/napari-kld/</link>
    <description>Recent updates to the Python Package Index for napari-kld</description>
    <language>en</language>    <item>
      <title>1.1.0</title>
      <link>https://pypi.org/project/napari-kld/1.1.0/</link>
      <description>Kernel learning deconvolution (KLD) is a rapid deconvolution algorithm for fluorescence microscopic image, which learns the forward and backward kernels in Richardson-Lucy Deconvolution (KLD) from paired low-/high-resolution images.</description>
<author>136303971@qq.com</author>      <pubDate>Mon, 05 Aug 2024 08:29:59 GMT</pubDate>
    </item>    <item>
      <title>1.0.2</title>
      <link>https://pypi.org/project/napari-kld/1.0.2/</link>
      <description>Kernel learning deconvolution (KLD) is a rapid deconvolution algorithm for fluorescence microscopic image, which learns the forward and backward kernels in Richardson-Lucy Deconvolution (KLD) from paired low-/high-resolution images.</description>
<author>136303971@qq.com</author>      <pubDate>Sat, 03 Aug 2024 02:55:43 GMT</pubDate>
    </item>    <item>
      <title>1.0.1</title>
      <link>https://pypi.org/project/napari-kld/1.0.1/</link>
      <description>Kernel learning deconvolution (KLD) is a rapid deconvolution algorithm for fluorescence microscopic image, which learns the forward and backward kernels in Richardson-Lucy Deconvolution (KLD) from paired low-/high-resolution images.</description>
<author>136303971@qq.com</author>      <pubDate>Fri, 02 Aug 2024 16:40:31 GMT</pubDate>
    </item>    <item>
      <title>1.0.0</title>
      <link>https://pypi.org/project/napari-kld/1.0.0/</link>
      <description>Kernel learning deconvolution (KLD) is a rapid deconvolution algorithm for fluorescence microscopic image, which learns the forward and backward kernels in Richardson-Lucy Deconvolution (KLD) from paired low-/high-resolution images.</description>
<author>136303971@qq.com</author>      <pubDate>Wed, 31 Jul 2024 16:16:39 GMT</pubDate>
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