Stride in Convolutional Neural Network (CNN)

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In this video, we will understand what is Stride in Convolutional Neural Network.

While performing Convolution operation on an image, we move our filter by 1 pixel. It is called having the stride = 1.

But it is also possible to move our filter by 2 pixels or 3 pixels or even more. This is called Strided Convolution in CNN.

Stride in Convolutional Neural Network defines the number of pixels we want to skip or move while performing Convolution Operation in CNN.

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Follow my entire playlist on Convolutional Neural Network (CNN) :

At the end of some videos, you will also find quizzes 📑 that can help you to understand the concept and retain your learning.

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You're underrated! Thank you for making the concepts very clear.

kmrudula

I started watching you from videos of ANN and I benefited a lot. Thank you for your content :)

beshoibotros

You forgot the mention why we use STRIDE

mshamirtaloo

Thankyou so much its helped alot i was confused about stride and paddinh but this playlist is a real problem solver

javaria_Ibrahim

i like how you explain the concepts very well, but one thing you are lacking is a proper definition, because many like me come here for exam preparation, so if you can give 1 or 2 line of definition (preferrably in a picture) show it few seconds and then explain the analogy of the concept, it would be a massive boost!!

opivcm

There was a glitch in the matrix @ 00:49

muralidhar

thankyou bro for the nice explanation. wish you more success

gladiatoralpha

You are very talented teacher. I am saying this as your colleague.

igorg

Hi bro! why do we need stride in CNN and how to decide how much to keep for what image? Should stride be neccesarily same in all dimensions? and what effect will it have if we keep it different in different dimensions

arpit

Do all images have to be converted to a square first?

John-wxzn

@coding lane - Can u pls share the PDFs for all the videos in this playlist. Even you u charge fee it is fine. Please share it.

adarshvadapalli

Kindly start making videos on computer vision especially on YOLO.

waleedrafi

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