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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1611.09326/</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/1611.09326/feed.xml" rel="self" type="application/rss+xml" /><item><title>The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation — mentioned by axiom92</title><link>https://news.ycombinator.com/item?id=19972840</link><guid isPermaLink="false">urn:hackerpapers:mention:1611.09326:19972840</guid><pubDate>Tue, 21 May 2019 18:01:34 GMT</pubDate><description>&lt;p&gt;&amp;gt; They are large, but far from overflowing. Sure, but isn&amp;#x27;t large relative? Sure you can make them overflow in octave as well, given enough layers. Which brings us to next point :-) &amp;gt; And this corresponds to a network of deep 100, which is not a realistic scenario. Actually deep 100 is not unrealistic at all these days! https://arxiv.org/abs/1611.09326&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1611.09326/"&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>
