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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Fully Convolutional Networks for Semantic Segmentation · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1605.06211/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/1605.06211/feed.xml" rel="self" type="application/rss+xml" /><item><title>Fully Convolutional Networks for Semantic Segmentation — mentioned by ebalit</title><link>https://news.ycombinator.com/item?id=12846130</link><guid isPermaLink="false">urn:hackerpapers:mention:1605.06211:12846130</guid><pubDate>Tue, 01 Nov 2016 14:58:15 GMT</pubDate><description>&lt;p&gt;It has been done with manual segmentation [1]. And the results are mind blowing. There also a lot of work done on segmentation with neural nets [2, 3], so I wouldn&amp;#x27;t be surprised to see someone implementing this idea in the near future. 1: https://github.com/alexjc/neural-doodle 2: https://arxiv.org/pdf/1605.06211.pdf 3: http://mi.eng.cam.ac.uk/projects/segnet/&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1605.06211/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CV</category></item></channel></rss>
