Hello.
Welcome back.
When dealing with our Richie B call colored images the dimension of each input image is three dimensional
because the other three color Chanos red green and blue.
Because of this the dimension of the filter can or must also be three dimensional one filter for each
colour channel of the inputs image over here we can see a six by six by three inputs.
Image converged with a three by three by three filter Kanno.
The outputs shape will be four by four.
So the first element of the outputs is the sum of the elements Y's product of the first twenty seven
values from the input.
Remember nine values from each channel and the twenty seven values from the filter the two turn seven
values from the input and the twenty seven values from the filter gives us the first element of the
output.
After this we convert the whole image.
In this process also instead of using a single three dimensional filter we can use multiple three dimensional
filters as well.
We could do this because we want each three dimensional filter to detect a different type of feature.
For instance we want one filter can or two detect horizontal edges and another filter can or two detect
vertical edges.
In this instance the dimension of our output matrix will be four by four by two because we have two
outputs as we can see in this arrangement.
Over here we can generalize the equation of the output actually.
We can say if and see this the number of channels of the input image and NC Prime is the number of channels
of the film Kano one given an input image of size and by and by NC the output will be and plus two p
minus f divided by s plus one by and plus two p minus f divided by s plus one by number of channels
which is and primacy over here or NC prime number of channels of the fields.
I can't all right.
So that's all the risk for this lesson and I shall see you in the next lesson.