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So if we accept for the sake of argument the idea that fine-grained-visual-categorisation is a different task to generic object recognition and needs different algorithms as in [this Diettrich paper](…
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I was looking for an example (and some inspiration) to develop a general framework for a stacked autoencoder + classification solution in C# that would help reduce the ~100 numeric dimensions for a re…
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Hey!
I suggested this a while back, and I made some progress so I figured I would bring it up again. I implemented the marginalized stacked denoising autoencoder algorithm described in http://www.cs…
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- [ ] The proposed method in the paper is essentially the U-Net. Why is it branded differently ? What are the key differences (if at all) ?
- [ ] Table IV reports that Net12 performance better o…
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[You posted on Reddit](https://www.reddit.com/r/MachineLearning/comments/l4rnfv/p_why_are_stacked_autoencoders_still_a_thing/).
I think this is very cool.
In the Reddit post you ask if you misse…
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Although our existing kitchen-sink approach is unbiased, it may not make sense for all screens, and it places an unnecessary burden on investigators when they are applying our software to new screens.…
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[Visualizing Higher-Layer Features of a Deep Network](http://www.iro.umontreal.ca/~lisa/publications2/index.php/publications/show/247)
Deep architectures have demonstrated state-of-the-art results in…
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Hi! First question here :)
I'd like to ask one basic question, I use tiny-cnn for training images, and create network. After that I want to use it as feature extractor rather than classifier. The qu…
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Hi Marco,
Have you got any update about this replicating this?
I find this work very interesting for the probability to apply the method to nucleosynthesis network calculation.
Look forward to hea…
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https://dx.doi.org/10.1093/nar/gkv1025