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<oembed><version>1.0</version><provider_name>MTS</provider_name><provider_url>https://research.dii.unipd.it/mts</provider_url><author_name>sebastianochiodini</author_name><author_url>https://research.dii.unipd.it/mts/author/sebastianochiodini/</author_url><title>Vision-based Navigation - MTS</title><type>rich</type><width>600</width><height>338</height><html>&lt;blockquote class="wp-embedded-content" data-secret="VCv1meBs2c"&gt;&lt;a href="https://research.dii.unipd.it/mts/vision-based-navigation/"&gt;Vision-based Navigation&lt;/a&gt;&lt;/blockquote&gt;&lt;iframe sandbox="allow-scripts" security="restricted" src="https://research.dii.unipd.it/mts/vision-based-navigation/embed/#?secret=VCv1meBs2c" width="600" height="338" title="&#x201C;Vision-based Navigation&#x201D; &#x2014; MTS" data-secret="VCv1meBs2c" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"&gt;&lt;/iframe&gt;&lt;script type="text/javascript"&gt;
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</html><description>Vision-based proximity navigation between satellites In recent years, there has been an increasing interest in utilizing Artificial Intelligence algorithms for space applications. Among the spectrum of Machine Learning techniques available, Convolutional Neural Networks (CNNs) emerge as a well-suited deep learning approach for optimizing Guidance, Navigation, and Control systems during close-proximity operations between satellites.&nbsp; Our research&hellip; Leggi tutto</description><thumbnail_url>https://research.dii.unipd.it/mts/wp-content/uploads/sites/93/2024/02/Vision-based_overview.png</thumbnail_url></oembed>
