You would show many variants of the same object in a short period of time to the HTM. It will associate them together using temporal pooling, and that's what gives you an invariant representation. Basically, time acts as a supervisor to correlate the variations.
On Thu, Nov 14, 2013 at 1:36 PM, Dennis Stark <[email protected]> wrote: > > > Multiple cells per column offer variable order memory, while one cell > per column offers only first-order memory. However, first-order memory is > useful for static invariant pattern recognition, since it doesn't maintain > long context. This might be ideally suited for the image categorization > problem. > > > > From the whitepaper: "We have further observed that a region like this > exhibits stability to translation, changes in scale, etc. while maintaining > the ability to distinguish between different images. This behavior is what > is needed for spatial invariance (recognizing the same pattern in different > locations of an image)." > > > > So maybe try a one-cell-per-column region! > > This is exactly what got me excited. But I can't understand how that works > and why would that work. > > Example. > > I feed an image to a first order HTM. I get columns activated. So HTM > learns which columns represent this image. Now each cell (1 per column) is > connected to adjacent other cells as well. So when a rotated image comes > in, it activates new columns. Cells in those new columns have synapses to > cells in columns from the first image. I.e. their prediction is the > original variant of an image. But unless it is implicitly specified, those > synapses have no way of figuring this out. Again this is a problem of > showing an HTM every possible size and angle to ensure invariance. > I wish I'd understand where the invariance comes from, without exposure to > every possible combination which can be a huge number of combinations. > > > > _______________________________________________ > nupic mailing list > [email protected] > http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org >
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