How can I fixed the filter and Kernel Size of a CNN?

I have created 4 x 4 2d images from a signal. Now, I want to feed this data to a Convolutional neural Network. How I can choose the nubmber of filter, Kernel Size for this small, shape and size of dataset (4 x 4, 320 images). Should I use maxpooling layer ?

Note: I have already implemented a model for this dataset and accuracy is 78.125%. The model is,

Topic cnn keras tensorflow deep-learning neural-network

Category Data Science

1
answered at

Since the images are just 4x4 in size, you can do the following :

  • You can resize the image to a much larger dimension like 28x28 and then use sharpen or histogram equalization to bring out the contrast. Then use a 3x3x16, 3x3x 32 kernel arrays in 2 convolutional layers. The rest is fully connected.

  • The images can be input as 4x4 images but use a shorter neural net. One convolutional layer with padding and 3x3x 32 shape would do.

  • Use something similar to google nets, inception module, in which output from multiple convolutions are combined.

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