Tag: neural networks
-
Giving up on the convolutional network?
For almost three months now I have been trying to build and train a convolutional network that will recognise chess puzzles: but I don’t feel I am any closer to succeeding with it than I was at the start of September and so I wonder if I should just give up. The network itself is…
-
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…
-
Strange reviews on Amazon
Messing about with convolutional neural networks (CNNs) continues to take up some of my time (in case my supervisor reads this – I also have a simulation of a many core system running on the university’s computer atm). I started my research here with a much cited, but really well-out-0f-date book – Practical Neural Network Recipes…
-
Free software to chop up your JPEGs
As a public service announcement – if you need some software (on Linux but may well compile and run on other systems if they support Qt) to chop a big JPEG up into smaller files, I have written this (in my case to support building a test set for a neural network). It’s at https://github.com/mcmenaminadrian/TestSetCreator and…
-
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…
-
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…
-
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…
-
Back to neural networks
Neural networks have fascinated me for a long time, though I’ve never had much luck applying them. Back in the early and mid 1990s the UK’s trade and industry department ran a public promotional programme to industry about NNs and I signed up, I even bought a book about how to build them in C++…
-
Predicting political outcomes with neural nets
View image | gettyimages.com The application of neural networks to politics has long been a personal interest – but until today that’s all it has been – an interest, not anything pursued practically. My initial inspiration – more than twenty years ago – was the simple insight that, when canvassing for votes you often know…
cartesian product ... stuff about computing mostly 