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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>TernausNetV2: Fully Convolutional Network for Instance Segmentation · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1806.00844/</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/1806.00844/feed.xml" rel="self" type="application/rss+xml" /><item><title>TernausNetV2: Fully Convolutional Network for Instance Segmentation — mentioned by nl</title><link>https://news.ycombinator.com/item?id=17484530</link><guid isPermaLink="false">urn:hackerpapers:mention:1806.00844:17484530</guid><pubDate>Sun, 08 Jul 2018 16:20:59 GMT</pubDate><description>&lt;p&gt;Have you released pre-trained models? It would be pretty useful if you did, even as a just basis for transfer learning. Also a description of the model that is used? I assume this is the code[1], which references https://arxiv.org/abs/1806.00844, but the code doesn&amp;#x27;t seem to use WideResnet (although I really know Keras much better than PyTorch so I&amp;#x27;m probably missing something. [1] https://github.com/mapbox/robosat/blob/master/robosat/unet.p...&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1806.00844/"&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>
