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Now, one of the problems that originate with large strayed is that we may not be able to cover the

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entire image.

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For example, you're just trying to cover this image with a five by five window moving with a straight

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of three.

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So the first neuron covers these first twenty five pixels.

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Now, in the next trade, we will cover these next twenty five pixels.

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So we have this trade of three after the fourth pixel.

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We got another twenty five pixels and so on.

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At this point where are neuron is seeing these 25 pixels.

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Now, in the next raid, we do not have quantified pixels.

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We will be out of pixel columns which can be covered.

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So if I take next raid, there are only 20 pixels available and not 25.

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This is a problem because we want uniformity.

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That is each neuron should have seem receptive field of 25 pixels.

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In this situation, we have two options.

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First option is to ignore these extra pixels at the border.

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So since we cannot cover the last two pixel columns, we leave out one pixel column from left and one

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pixel column on the right.

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So instead of a 16 by 16 image, we will consider only a 14 by 14 image, one line of pixel remove from

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all the eight.

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This 14 by 14 image can be covered with a fiber five window.

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And a street of three.

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This particular option.

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It's called Valid Birdying.

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Which actually means that we are not using any padding.

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And that we only use valid window locations and ignore the extra pixels at the border.

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Second option is adding extra rows and columns of dummy pixels or black pixels.

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For example, here we add one more layer of pixels.

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We can then move forward with a straight of three.

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And the last neutron will also have a view peeled off twenty five pixels grindy from the original image

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and five offer artificially generated blank pixels.

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This type of padding is called same padding, which means bad in such a way so as to have an output

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which can be covered by a window of same Bertan height.

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By default, batting arguments in our software are said to be valid if you think the border of your

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image stores important information in those scenarios only we will change this parameter to saying it's

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valid works well.

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Here is the definition of two arguments that we have covered.

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First, it straight straight denotes how many steps we take in each step of convolution.

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So in the first step, that is our first neuron is looking at this red rectangle.

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And the second neuron is looking at this blue rectangle.

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Then we have strayed off to.

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We can specify both horizontal and vertical strait separately.

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By default, straight value is set at one.

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The second concept that we discussed is of buiding.

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Padding is the process of adding zeros to the input image to maintain the dimension of output as an

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input.

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If we decide to ignore the border values, which could not be covered due to our large trade, in that

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case, we are not using any padding for which the argument is valid burning.

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If we are adding additional black pixels so that our window can cover the border pixels, also in that

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scenario, we are using same padding.

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So these are the two arguments that we will need to specify when we train our convolutional leered.