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      <title>Deep learning–based automated measurements of the scrotal circumference of Norwegian Red bulls from 3D images</title>
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&lt;p&gt;Working on Computer Vision tasks is always exciting for me. During my carrier I was working with many different types of images and was solving many different problems related to them in the fields of biology, medicine, genetics, climatology and many more. Today I would like to tell you about one of the most extraordinary use cases I’ve ever worked on.&lt;/p&gt;
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      <title>Explaining predictions of Convolutional Neural Networks with &#39;sauron&#39; package.</title>
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      <pubDate>Sun, 10 Jan 2021 01:00:00 +0000</pubDate>
      
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&lt;p&gt;Explainable Artificial Intelligence, or &lt;strong&gt;XAI&lt;/strong&gt; for short, is a set of tools that helps us understand and interpret complicated &lt;strong&gt;“black box”&lt;/strong&gt; machine and deep learning models and their predictions. In my previous post I showed you a sneak peek of my newest package called &lt;strong&gt;sauron&lt;/strong&gt;, which allows you to explain decisions of Convolutional Neural Networks. I am really glad to say that beta version of &lt;strong&gt;sauron&lt;/strong&gt; is finally here!&lt;/p&gt;
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