How to apply CNN for multi-channel pixel data based weights to each channel?

I have an image with 8 channels.I have a conventional algorithm where weights are added to each of these channels to get an output as '0' or '1'.This works fine with several samples and complex scenarios. I would like implement the same in Machine Learning using CNN method.

I am new to ML and started looking out the tutorials which seem to be exclusively dealing with image processing problems- Hand writing recognition,Feature extraction etc.

http://cv-tricks.com/tensorflow-tutorial/training-convolutional-neural-network-for-image-classification/

https://leonardoaraujosantos.gitbooks.io/artificial-inteligence/content/neural_networks.html

I have setup the Keras with Theano as background.Basic Keras samples are working without problem.

What steps do I require to follow in order achieve the same result using CNN ? I do not comprehend the use of filters,kernels,stride in my use case.How do we provide Training data to Keras if the pixel channel values and output are in the below form?

Pixel#1 f(C1,C2...C8)=1

Pixel#2 f(C1,C2...C8)=1

Pixel#3 f(C1,C2...C8)=0 .

.

Pixel#N f(C1,C2...C8)=1