https://openclassrooms.com/fr/courses/5801891-initiez-vous-au-deep-learning

Initiez-vous au Deep Learning

We may introduce multiple convolution filters, e.g., one for vertical and the other one for horizontal edge detection. This way, convolving the image with each filter will give us one output matrices that we can also stack as a volume.

University of Michigan - Ann Arbor

For example, if we have a 3 x 3 x 3 RGB filter, to perform the convolution operation, we start with placing the filter in the upper left most position of the image. We can consider this 3 x 3 x 3 filter as a cube with 27 parameters, where the first dimension is called "width," the second is called height, and the third indicates the number of channels. We multiply each of these 27 numbers with the corresponding numbers from the red, green, and blue channels of the image and sum up the results to calculate the corresponding output number. Then to compute the next output, we take this cube and slide it over by one, do the 27 multiplications, and add up the results to calculate the next output number, and so on. This way, convolving a 6 x 6 x 3 image with a 3 x 3 x 3 filter will give us a 4 x 4 output.

Convolutions Over Volumes

https://blog.roboflow.com/when-to-use-grayscale-as-a-preprocessing-step/

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