For vision:
http://www.matthewzeiler.com/pubs/iccv2011/iccv2011.pdf
http://people.idsia.ch/~ciresan/data/icann2011.pdf
On 04/09/2015 12:56 PM, Eraldo Pomponi wrote:
Dear Andy,
On Thu, Apr 9, 2015 at 2:56 PM, Andy <t3k...@gmail.com
<mailto:t3k...@gmail.com>> wrote:
Hi Dan.
Scikit-learn focuses on "flat" signals and algorithms and we don't
usually add algorithms on time-series or nd-data,
as that would significantly widen the scope and complicate API.
Maybe we
should add this to the FAQ.
FWIW I didn't have a very good experience when working with
convolutional (shouldn't it be that?) NMF.
Why no use an autoencoder approach?
Sorry for being dense here but would you elaborate a little bit more
what you
are suggesting?
Maybe pointing me to a similar application of an autoencoder could
help a lot.
Thanks in advance.
Eraldo
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