Tag: Image processing
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Can you get a useful result with a random convolution filter?
In a number of places I’ve seen it remarked that a random convolution filter makes for a reasonably efficient edge detector for images, so I thought I’d test this. The answer, perhaps surprisingly, seems to be yes. With 25 input filters in an untrained convolutional neural net (where kernel values were pseudo-randomly distributed between -0.5…
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Even more about neural networks
Because I essentially got it wrong in the last post … turns out that a fully connected network is, generally, not a great idea for image processing and that partial connections – through “convolution layers” are likely to be more efficient. And my practical experience backs this up: my first NN did, in effect, have…
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Learning more about neural networks
Cheap and accessible books on neural nets are not easy to find – so I bought “Practical Neural Network Recipes in C++” as a second-hand book on Amazon (link). According to Google Scholar this book – though now 24 years old – has over 2,000 citations, so it ought to be good, right? Well, the…
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First results from the “musical” neural network
I am working on a project to see whether, using various “deep learning” methods, it is possible to take a photograph of some musical notation and play it back. (I was inspired to do this by having a copy of 1955’s Labour Party Songbook and wondering what many of the songs sounded like.) The first task…
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“Let’s enhance that” might work after all
This video has amused and fascinated many because it displays a fundamental ignorance of a basic rule of the – universe – a consequence of the second law of thermodynamics – that one cannot extract more information out of a picture than went into it at the time of creation: But, according to the “Communications…
cartesian product ... stuff about computing mostly 