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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Multiple Object Recognition with Visual Attention · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1412.7755/</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/1412.7755/feed.xml" rel="self" type="application/rss+xml" /><item><title>Multiple Object Recognition with Visual Attention — mentioned by radarsat1</title><link>https://news.ycombinator.com/item?id=10893999</link><guid isPermaLink="false">urn:hackerpapers:mention:1412.7755:10893999</guid><pubDate>Wed, 13 Jan 2016 13:15:06 GMT</pubDate><description>&lt;p&gt;This would be quite a cool problem to attack using RNN. Perhaps using an attention-following mechanism like the one used for house numbers [1]. It&amp;#x27;s fairly well-defined. You would need a ton of example data though. [1] http://arxiv.org/abs/1412.7755&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1412.7755/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item></channel></rss>
