Is it possible, for a limited dateset of images, to use Convolution filters + Random Forest instead of UNet?

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How can I setup the Wray1997 Decaying Isotropic Turbulence benchmark case?

As a phD researcher, I am trying to validate my solver through use of decaying isotropic turbulence. I preferred to use the Wray1997 data, which would be a good step towards evaluating my solver's...

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What are the values needed for gabor filter's parameter for cifar10 data?

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03 March 2021 6,317 1 View

How to calculate Total Flavonoid?

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Can random sampling have inclusion criteria?

As random sampling means that everyone in the population have an equal chance to be chosen, can it have inclusion criteria? My research participants have been chosen based on the inclusion...

26 February 2021 6,905 10 View

RNA-seq DEGs downstream analysis and reporting in literature?

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What are the ranges of four diffterent poles of butterworth filter for ECG signal?

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23 February 2021 2,554 3 View

Which polarizers are usually used to measure the birefringence of zebrafish muscles?

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23 February 2021 1,934 1 View

What low-cut filter (high Pass frequency) to be used for response spectrum (Tripartite plots) ?

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The type of filter paper used to filter an epoxidized oil (the mixture is an epoxidized oil with magnesium sulfate) ?

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Algorithms to filter corrective max and min from a set of data?

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17 February 2021 2,777 5 View

Using 1D CNN for pixel classification in an image?

I have a 3D Image of size 100x100x100. I have features (feature dimension 25) extracted for each pixel by considering a small pacth around it. So the input to 1D CNN is 100x100x100x25 reshaped to...

17 February 2021 941 4 View

Aakarsh Malhotra

Yes, of course it is.

You may use any pre-trained network like VGG16, ResNet50 and obtain its feature representation from the last conv layer. (For VGG, it is after the global average pooling layer). Use that representation to train an RDF classifier for your classification task.

Also, this approach works best if the images are very less. If you have even around ~1000 images, try training/fine-tuning the networks.