Adam, This is a very interesting and useful paper, thanks for linking.
- Chetan On Thu, Mar 13, 2014 at 3:35 PM, Adam Kneller < [email protected]> wrote: > Hi, > > My supervisor is the lead author on that paper. It uses the old version of > the HTM, not the CLA. We have some more recent papers dealing with digit > recognition that use the CLA, e.g. Evaluating Sparse Codes on Handwritten > Digits (http://link.springer.com/chapter/10.1007/978-3-319-03680-9_40). > > Let me know if you don't have Springer access and I will hopefully be able > to get yo a copy. > > Adam. > > > On 13 March 2014 01:36, Traun Leyden <[email protected]> wrote: > >> >> Yep, fair enough. It sounds like you would need more than just a spatial >> pooler here. >> >> I've found this paper which seems to be trying to tackle the same >> problem: http://www.ict.griffith.edu.au/~johnt/publications/AI2008.pdf >> >> but unfortunately don't know where the accompanying source code is (or if >> it's available). >> >> Btw if you think this repo would be good to put in the examples >> directory, I'd be happy to send a PR. >> >> >> On Mon, Mar 10, 2014 at 8:33 AM, Matthew Taylor <[email protected]> wrote: >> >>> To quote Subutai from another thread [1]: >>> >>> "You might not get an exact match unless the inputs are really really >>> close. In particular, the spatial pooler won't do too well at learning >>> general invariances (and it's not supposed to). For example, if you >>> shift the image by one or two pixels you might get a very different >>> output SDR." >>> >>> [1] http://markmail.org/message/dytllixwodm5bjcu >>> --------- >>> Matt Taylor >>> OS Community Flag-Bearer >>> Numenta >>> >>> >>> On Sun, Mar 9, 2014 at 12:27 PM, Traun Leyden <[email protected]> >>> wrote: >>> > >>> > I created a simple example to recognize digits using the spatial >>> pooler, >>> > it's available on github here: >>> > >>> > https://github.com/tleyden/nupic-digitrecognizer >>> > >>> > It was able to get exact matches with SDR's, and I didn't need to use >>> the >>> > KNNClassifier. Having said that, the test data was relatively "easy", >>> in >>> > that I just went through the training data and removed a few pixels. >>> > >>> > However when I tried to recognize a digit that's been entirely shifted >>> to >>> > the right by a few pixels (original - shifted) it wasn't able to find a >>> > match. >>> > >>> > What are some suggested approaches to add spatial invariance so it can >>> > handle this? >>> > >>> > I did see this mailing list thread but so far no simple answer has >>> jumped >>> > out at me. >>> > >>> > Also thanks to all the folks who responded to my questions, those were >>> > useful pointers. >>> > >>> > >>> > >>> > _______________________________________________ >>> > nupic mailing list >>> > [email protected] >>> > http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org >>> > >>> >>> _______________________________________________ >>> nupic mailing list >>> [email protected] >>> http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org >>> >> >> >> _______________________________________________ >> nupic mailing list >> [email protected] >> http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org >> >> > > _______________________________________________ > nupic mailing list > [email protected] > http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org > >
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