Deep Belief Network on CIFAR-10
€30-250 EUR
Dibayar saat pengiriman
The database of CIFAR-10 can be found on this page (CIFAR-10 Matlab version) : [login to view URL]~kriz/[login to view URL]
The algorithm theory is based on MSc thesis of Alex Krizhevsky (Learning Multiple Layers of Features from Tiny Images).
The paper can be found in the bottom of the same page ([login to view URL]~kriz/[login to view URL])
1) The developer must first download the database
2) Implement ZCA whitenning transformation to the data
3) Create a 2-layer (2 is the number of stacked Gaussian - Bernoulli Boltzman machines).
4) Train the Deep Belief Network using greedy layer-wise method
5) Train each Boltzman machine with CD (contrastive divergence) method
6) Extract an error on train images
* Extract some images of the filters from 1-layer
* Extract some images of the filters from 2-layer
The algorithm must be as simple and readable as possible and well commented in Matlab, impmlemented for ECU not GPU.
All informations are in the paper of Alex Krizhevsky.
ID Proyek: #8920255
Tentang proyek
4 freelancer rata-rata menawar €559 untuk pekerjaan ini
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