Padding in Convolutional Neural Network

In this video, we will understand what is Padding in Convolutional Neural Network and why do we need padding in Convolutional Neural Network
Convolution Operation faces two problems:
1.) The size of the image gets reduced after performing Convolution operation
2.) Corner pixels of the input image doesn't get enough attention as the pixels around the center
Thus, to overcome these issues, we use padding in convolutional neural network
In the video, we will understand what is "VALID" Convolution and what is "SAME" Convolution. And we will also discuss the dimensions of the image after applying padding.
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Timestamp:
0:00 Intro
0:11 The Problem with convolution operation
1:15 Padding in Convolutional Neural Network
2:05 Types of Padding
3:42 End
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[@mariamhm]

Hi!, I just wanted to tell you that your channel saved my academic life
I don't have enough words to express how thankful I am. Thank you very much for this great, clear, and straightforward explanation!

[@CodingLane]

Hey, I am elated. Glad I could help. All the best for future!

[@Ramu9119]

thanks for the video champ

[@jaisarita]

Really nice explanation ❤

[@williammartin4416]

Thanks!

[@user-xx4sl1qk1o]

genius genius broooooooooo

[@DJKim-pq5rn]

wow this is a great video

[@raskirocks]

You are doing a great job. Keep uploading new videos.

[@CodingLane]

Thank you

[@deepthitulluru5584]

Can you provide any notes about all this convultion neural networks
That might help for my project
Any ways nice explanation & content bro

[@shahidulislamzahid]

Helpful! Thank you.

[@CodingLane]

Welcome!

[@Sickkkkiddddd]

Maaaaaaaaaan, you make this stuff really simple... sigh. Its a relief.
Edit: please use a white marker next time on your black background.

[@danyalkhan8923]

Thanks g

[@AnkitaKumari-hw8bx]

Plz upload more frequently,t's really easy for us to understand from your teaching

[@CodingLane]

Thank you so much! I will do my best to upload more frequently. I have already increased my uploading frequency from 1 video/week to 2 videos/week. 🙂

[@malikhamza9286]

Amazing videos

[@CodingLane]

Thanks for your continuous support

[@sihatafnan5450]

Great content
just one suggestion, red pen over black background isnt a good choice

[@mugomuiruri2313]

good

[@Miss_Md]

Thanx

[@CodingLane]

😇

[@mohammedamirjaved8418]

Bubber Shair veer.....Shahzada

[@CodingLane]

Thank you 😁😇

[@Seba_Crea]

👍

[@yatinarora9650]

you should have added, If kernel size is non-symetric matrix then how to do padding

[@CodingLane]

Okay thanks for the suggestion 😇… will try to add it in the future video

[@requanmoseni7027]

I have a question,,yes padding is important in giving corner pixels much attention as the middle pixels in filter wimdow,,,but then doesnt make the process of convolution invalid because the output image is same as input image??? And the whole purpose of convolution is to reduce the size of input image

[@magmanik5833]

I'm guessing that's the point of maxpooling, since pooling is always applied after convolution. The thing is that idk when people would use paddling and when they wouldn't, since it makes sense to always use it at least for the first layer.

[@ANILKUMAR-mn7pk]

let 4*4 pixel and we add 1 padding then it become 6*6 and filter of 2*2 then output dimension will be 5*5 but we want 4*4 output.....this is my doubt

[@WOLVERINE-15]

if you want same image dim with filter having even dim (i.e 2*2), need to apply uneven padding (i.e 0 on left and 1 on right, same with top and bottom => now image will be 5*5)

[@aniket_kalta]

Apply 3*3 filter to get 4*4 pixel image

[@requanmoseni7027]

I think what you're asking is how can we know what filter size to apply to input image to get output image of same dimension as input image????