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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Deep neural network-based detection of counterfeit products from smartphone images · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2410.05969/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:27:26 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2410.05969/feed.xml" rel="self" type="application/rss+xml" /><item><title>Deep neural network-based detection of counterfeit products from smartphone images — HN submission</title><link>https://news.ycombinator.com/item?id=44594017</link><guid isPermaLink="false">urn:hackerpapers:submission:2410.05969:44594017</guid><pubDate>Thu, 17 Jul 2025 14:47:39 GMT</pubDate><description>&lt;p&gt;Ask HN : AI to Detect Counterfeit Adderall&lt;/p&gt;&lt;p&gt;We developed an AI capable of detecting counterfeit products from a picture of the box taken with a smartphone. I know it sounds like witchcraft, but after 6 years of research it actually works even on super fakes, even in tough conditions : https://arxiv.org/abs/2410.05969 We&amp;#x27;re thinking on which product to protect next, the goal being to make an app available to the general US public to test the meds they buy online. Do any of you buy Adderall online ? If yes how interested would you be in making sure that it&amp;#x27;s not counterfeit before using it ? If anyone else buys medicine online but it&amp;#x27;s…&lt;/p&gt;&lt;p&gt;2 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2410.05969/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.CV</category></item></channel></rss>
