<rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Hacker News: argilium</title><link>https://news.ycombinator.com/user?id=argilium</link><description>Hacker News RSS</description><docs>https://hnrss.org/</docs><generator>hnrss v2.1.1</generator><lastBuildDate>Thu, 23 Apr 2026 10:51:34 +0000</lastBuildDate><atom:link href="https://hnrss.org/user?id=argilium" rel="self" type="application/rss+xml"></atom:link><item><title><![CDATA[New comment by argilium in "Ask HN: What are you working on? (February 2026)"]]></title><description><![CDATA[
<p>Building a simple iOS app that's free (ad supported) for tracking expenses/receipts. Everything out there was subscriptions and I didn't want another monthly expense to track my simple expenses ...
<a href="http://loomlabs.au/docket" rel="nofollow">http://loomlabs.au/docket</a></p>
]]></description><pubDate>Mon, 09 Feb 2026 22:23:10 +0000</pubDate><link>https://news.ycombinator.com/item?id=46952380</link><dc:creator>argilium</dc:creator><comments>https://news.ycombinator.com/item?id=46952380</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=46952380</guid></item><item><title><![CDATA[We Hacked Companies in 30 Minutes Using a Fake VSCode Extension]]></title><description><![CDATA[
<p>Article URL: <a href="https://medium.com/@amitassaraf/the-story-of-extensiontotal-how-we-hacked-the-vscode-marketplace-5c6e66a0e9d7">https://medium.com/@amitassaraf/the-story-of-extensiontotal-how-we-hacked-the-vscode-marketplace-5c6e66a0e9d7</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=40665294">https://news.ycombinator.com/item?id=40665294</a></p>
<p>Points: 6</p>
<p># Comments: 1</p>
]]></description><pubDate>Thu, 13 Jun 2024 02:17:31 +0000</pubDate><link>https://medium.com/@amitassaraf/the-story-of-extensiontotal-how-we-hacked-the-vscode-marketplace-5c6e66a0e9d7</link><dc:creator>argilium</dc:creator><comments>https://news.ycombinator.com/item?id=40665294</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=40665294</guid></item><item><title><![CDATA[Eduard: Swiss-Style Relief Shading for Maps Using Machine Learning]]></title><description><![CDATA[
<p>Article URL: <a href="https://dilpreet.co/projects/eduard">https://dilpreet.co/projects/eduard</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=34919659">https://news.ycombinator.com/item?id=34919659</a></p>
<p>Points: 227</p>
<p># Comments: 74</p>
]]></description><pubDate>Fri, 24 Feb 2023 01:49:46 +0000</pubDate><link>https://dilpreet.co/projects/eduard</link><dc:creator>argilium</dc:creator><comments>https://news.ycombinator.com/item?id=34919659</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=34919659</guid></item><item><title><![CDATA[Eduard: Swiss-Style Relief Shading Using Machine Learning]]></title><description><![CDATA[
<p>Article URL: <a href="https://dilpreet.co/projects/eduard">https://dilpreet.co/projects/eduard</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=34770476">https://news.ycombinator.com/item?id=34770476</a></p>
<p>Points: 2</p>
<p># Comments: 1</p>
]]></description><pubDate>Mon, 13 Feb 2023 05:31:46 +0000</pubDate><link>https://dilpreet.co/projects/eduard</link><dc:creator>argilium</dc:creator><comments>https://news.ycombinator.com/item?id=34770476</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=34770476</guid></item><item><title><![CDATA[Searching for Visually Similar Artworks]]></title><description><![CDATA[
<p>Article URL: <a href="http://ai.sensilab.monash.edu/2018/09/17/similarity-search-engine/">http://ai.sensilab.monash.edu/2018/09/17/similarity-search-engine/</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=18050411">https://news.ycombinator.com/item?id=18050411</a></p>
<p>Points: 33</p>
<p># Comments: 2</p>
]]></description><pubDate>Sun, 23 Sep 2018 10:33:47 +0000</pubDate><link>http://ai.sensilab.monash.edu/2018/09/17/similarity-search-engine/</link><dc:creator>argilium</dc:creator><comments>https://news.ycombinator.com/item?id=18050411</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=18050411</guid></item><item><title><![CDATA[Show HN: Building content-based search for finding similar looking artworks]]></title><description><![CDATA[
<p>Article URL: <a href="http://ai.sensilab.monash.edu/2018/09/17/similarity-search-engine/">http://ai.sensilab.monash.edu/2018/09/17/similarity-search-engine/</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=18037256">https://news.ycombinator.com/item?id=18037256</a></p>
<p>Points: 5</p>
<p># Comments: 0</p>
]]></description><pubDate>Fri, 21 Sep 2018 05:02:19 +0000</pubDate><link>http://ai.sensilab.monash.edu/2018/09/17/similarity-search-engine/</link><dc:creator>argilium</dc:creator><comments>https://news.ycombinator.com/item?id=18037256</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=18037256</guid></item><item><title><![CDATA[Find Visually Similar Artworks Using Pre-Trained Neural Networks]]></title><description><![CDATA[
<p>Article URL: <a href="http://ai.sensilab.monash.edu/2018/09/17/similarity-search-engine/">http://ai.sensilab.monash.edu/2018/09/17/similarity-search-engine/</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=18011132">https://news.ycombinator.com/item?id=18011132</a></p>
<p>Points: 2</p>
<p># Comments: 0</p>
]]></description><pubDate>Mon, 17 Sep 2018 23:48:16 +0000</pubDate><link>http://ai.sensilab.monash.edu/2018/09/17/similarity-search-engine/</link><dc:creator>argilium</dc:creator><comments>https://news.ycombinator.com/item?id=18011132</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=18011132</guid></item><item><title><![CDATA[Thinking about how we think about machines that think]]></title><description><![CDATA[
<p>Article URL: <a href="http://ai.sensilab.monash.edu/2018/08/13/Lets-get-meta/">http://ai.sensilab.monash.edu/2018/08/13/Lets-get-meta/</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=17747887">https://news.ycombinator.com/item?id=17747887</a></p>
<p>Points: 3</p>
<p># Comments: 0</p>
]]></description><pubDate>Mon, 13 Aug 2018 03:41:55 +0000</pubDate><link>http://ai.sensilab.monash.edu/2018/08/13/Lets-get-meta/</link><dc:creator>argilium</dc:creator><comments>https://news.ycombinator.com/item?id=17747887</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=17747887</guid></item><item><title><![CDATA[Some things change, some not so much]]></title><description><![CDATA[
<p>Article URL: <a href="http://dilpreetsingh.me/photography/some-things-change-some-not-so-much">http://dilpreetsingh.me/photography/some-things-change-some-not-so-much</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=17622511">https://news.ycombinator.com/item?id=17622511</a></p>
<p>Points: 1</p>
<p># Comments: 0</p>
]]></description><pubDate>Fri, 27 Jul 2018 00:20:49 +0000</pubDate><link>http://dilpreetsingh.me/photography/some-things-change-some-not-so-much</link><dc:creator>argilium</dc:creator><comments>https://news.ycombinator.com/item?id=17622511</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=17622511</guid></item><item><title><![CDATA[DeeperDrake: LSTM trained on Drake that responds when you tweet to it]]></title><description><![CDATA[
<p>Article URL: <a href="http://twitter.com/deeperdrake">http://twitter.com/deeperdrake</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=11964641">https://news.ycombinator.com/item?id=11964641</a></p>
<p>Points: 1</p>
<p># Comments: 0</p>
]]></description><pubDate>Thu, 23 Jun 2016 22:06:25 +0000</pubDate><link>http://twitter.com/deeperdrake</link><dc:creator>argilium</dc:creator><comments>https://news.ycombinator.com/item?id=11964641</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=11964641</guid></item><item><title><![CDATA[DeeperDrake: LSTM trained on Drake that responds when you tweet to it]]></title><description><![CDATA[
<p>Article URL: <a href="https://twitter.com/deeperdrake">https://twitter.com/deeperdrake</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=11960774">https://news.ycombinator.com/item?id=11960774</a></p>
<p>Points: 2</p>
<p># Comments: 0</p>
]]></description><pubDate>Thu, 23 Jun 2016 13:47:14 +0000</pubDate><link>https://twitter.com/deeperdrake</link><dc:creator>argilium</dc:creator><comments>https://news.ycombinator.com/item?id=11960774</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=11960774</guid></item><item><title><![CDATA[New comment by argilium in "Recognising gym excerises in real-time using a neural network"]]></title><description><![CDATA[
<p>I never even considered logistic regression for this problem. Now that you've pointed it out, I'm going to look into.<p>Neural networks aren't really core part of the system. As long as I can get good + quick results, I'm really open to swapping out the learning algorithm.</p>
]]></description><pubDate>Mon, 19 Oct 2015 01:26:29 +0000</pubDate><link>https://news.ycombinator.com/item?id=10410596</link><dc:creator>argilium</dc:creator><comments>https://news.ycombinator.com/item?id=10410596</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=10410596</guid></item><item><title><![CDATA[New comment by argilium in "Recognising gym excerises in real-time using a neural network"]]></title><description><![CDATA[
<p>That's a good question. I'm also quite sick of all the logging apps that have their own unique formats.<p>If there is a standard out there, I'll definitely look at integrating that for the output.</p>
]]></description><pubDate>Mon, 19 Oct 2015 00:45:29 +0000</pubDate><link>https://news.ycombinator.com/item?id=10410489</link><dc:creator>argilium</dc:creator><comments>https://news.ycombinator.com/item?id=10410489</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=10410489</guid></item><item><title><![CDATA[New comment by argilium in "Recognising gym excerises in real-time using a neural network"]]></title><description><![CDATA[
<p>This is part of my honours thesis for my comp-sci degree. Once i've completed that, i'll definitely look at open sourcing.</p>
]]></description><pubDate>Mon, 19 Oct 2015 00:44:14 +0000</pubDate><link>https://news.ycombinator.com/item?id=10410480</link><dc:creator>argilium</dc:creator><comments>https://news.ycombinator.com/item?id=10410480</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=10410480</guid></item><item><title><![CDATA[New comment by argilium in "Recognising gym excerises in real-time using a neural network"]]></title><description><![CDATA[
<p>You're right on the ball. I'm indeed using temporal features to classify, along with various other statistical ones.<p>The repetition counting in my next aim. Once apple opens up the gyro on the Watch, I think there could be a good chance to get something like this out the door.</p>
]]></description><pubDate>Mon, 19 Oct 2015 00:42:32 +0000</pubDate><link>https://news.ycombinator.com/item?id=10410477</link><dc:creator>argilium</dc:creator><comments>https://news.ycombinator.com/item?id=10410477</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=10410477</guid></item><item><title><![CDATA[New comment by argilium in "Recognising gym excerises in real-time using a neural network"]]></title><description><![CDATA[
<p>You're right that I could get just as good results with other potentially faster algorithms but those algorithms don't afford me the ability (especially decision trees) to personalise.<p>The system is designed to be personalised. So for example if it's not doing well in recognising your squats for instance, you can immediately 'show' it what they look like. A neural network can immediately integrate that, and spit out great accuracy levels. Whilst i'd have to reconstruct a decision tree each time.</p>
]]></description><pubDate>Mon, 19 Oct 2015 00:40:21 +0000</pubDate><link>https://news.ycombinator.com/item?id=10410474</link><dc:creator>argilium</dc:creator><comments>https://news.ycombinator.com/item?id=10410474</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=10410474</guid></item><item><title><![CDATA[New comment by argilium in "Recognising gym excerises in real-time using a neural network"]]></title><description><![CDATA[
<p>That's a good question! Turkish Getup's are very complex like you say. Given my current setup and window length, it's unlikely that it'll recognise them, because one rep is very long. Maybe if I did exercise based window lengths it could work better? I'm honestly not sure. But that is something to try out!</p>
]]></description><pubDate>Sun, 18 Oct 2015 13:24:58 +0000</pubDate><link>https://news.ycombinator.com/item?id=10408164</link><dc:creator>argilium</dc:creator><comments>https://news.ycombinator.com/item?id=10408164</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=10408164</guid></item><item><title><![CDATA[New comment by argilium in "Recognising gym excerises in real-time using a neural network"]]></title><description><![CDATA[
<p>That's an interesting point. The problem here would be that video input would not provide accel+gryo motion information, which is what the network needs in order to learn.<p>If we instead simply used video information to track exercises the problem would be scaling that to consumers. They'd require an external camera to watch them.<p>But the idea of using Mechanical Turk is quite smart. It'd help me get varied form - especially if I can get them to wear a band/phone that has the sensors.</p>
]]></description><pubDate>Sun, 18 Oct 2015 13:20:34 +0000</pubDate><link>https://news.ycombinator.com/item?id=10408151</link><dc:creator>argilium</dc:creator><comments>https://news.ycombinator.com/item?id=10408151</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=10408151</guid></item><item><title><![CDATA[Recognising gym excerises in real-time using a neural network]]></title><description><![CDATA[
<p>Article URL: <a href="http://dilpreetsingh.me/activity-recognition">http://dilpreetsingh.me/activity-recognition</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=10407944">https://news.ycombinator.com/item?id=10407944</a></p>
<p>Points: 56</p>
<p># Comments: 28</p>
]]></description><pubDate>Sun, 18 Oct 2015 11:38:44 +0000</pubDate><link>http://dilpreetsingh.me/activity-recognition</link><dc:creator>argilium</dc:creator><comments>https://news.ycombinator.com/item?id=10407944</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=10407944</guid></item><item><title><![CDATA[Recognising gym excerises in real-time using a neural network]]></title><description><![CDATA[
<p>Article URL: <a href="http://dilpreetsingh.me/activity-recognition">http://dilpreetsingh.me/activity-recognition</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=10403719">https://news.ycombinator.com/item?id=10403719</a></p>
<p>Points: 3</p>
<p># Comments: 0</p>
]]></description><pubDate>Sat, 17 Oct 2015 07:45:33 +0000</pubDate><link>http://dilpreetsingh.me/activity-recognition</link><dc:creator>argilium</dc:creator><comments>https://news.ycombinator.com/item?id=10403719</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=10403719</guid></item></channel></rss>