Convolution Operation in CNN

In this video, we will understand what is Convolution Operation in CNN. Convolution Operation is the heart of Convolutional Neural Network. It is responsible for detecting the edges or features of the image. The main reason for the good performance of Convolutional Neural Network is Convolution Operation.
With simple mathematics, you will understand how Convolution Operation in CNN is able to detect edges of the image. Then we will also discuss how the Convolution Operation is performed in a colored image.
This video will be a complete package to understand Convolution Operation in CNN.
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Timestamp:
0:00 Intro
1:26 Convolution Operation in CNN
4:07 Vertical Edge detection
6:21 Convolutional Layer
7:23 Convolution Operation for Colored Image
9:12 End
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📕 Sorry, the Assessment quiz was deleted due to a technical issue. I will upload it after some time.
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Follow my entire playlist on Convolutional Neural Network (CNN):
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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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✔ Complete Neural Network Playlist: • How Neural Networks wo...
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[@maharshitrivedi3749]

because of the graphics and visualization the concepts become more clear to me. thankyou for creating this content.

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[@CodingLane]

Yes… I will continue. Thank you so much!

[@devanshshah396]

By far the best explanation I have ever seen all over the internet. Respect _/\_

[@photorealm]

Very well explained, showing the resultant images with the edges made it all make sense. Thank yo9u for sharing.

[@pragya1tiwari]

Thank you for such crisp and to the point explanation. Being at an absolute beginner's level, this video was really helpful :)

[@TortoisesShell]

Amazing content and explanation, keep up the good work mate!

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[@CodingLane]

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Thanks pal! Brilliant explanation.

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😊

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This was such a practical explanation 👌👌👌

[@sujithsaikalakonda4863]

Wonderful explanation sir.

[@agogubaid2360]

You answered all my doubts that were raised during my learning of CNN. Thank you so much

[@CodingLane]

Glad to help :)

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Amazing explanation 🙌

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Helpful! Thank you.

[@CodingLane]

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[@CodingLane]

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[@arpit743]

hi!, why did the vertical edge detector capture some of the slanting and horizontal edges?

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great explaining

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[@CodingLane]

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great explaniation

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well taught, I learned

[@KomalSingh.87]

Where's the quiz?

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[@CodingLane]

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Great Explanation!
provide the link for quiz please!

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Really helpful

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quality content, hopefully u will get the more result soon.
kudos to you sir

[@CodingLane]

Thank you!

[@mahalakshmi5264]

Is there any way to put the values and change of filters?
How can we choose those filters?

[@fullseries2155]

Thank you sir

[@Name-yu6ux]

The filters have specific value and they can be used in any img?

[@rishikeshram574]

nice explanation ... but bro u must explain the difference between cross correlation and convolution.

[@poxato]

Hey man. thanks for making this video. but can you please re upload the quiz.

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Amazing, but i was curious to attend quiz, to know how much i have understood

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thank you

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[@artie5172]

How will there be many filters in a single layer ? Are the filters treated as weight in the cnn?

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[@vigilgeorge9508]

Thankyou

[@user-eu4sn5jg8p]

i had a doubt you mentioned gray scale goes from 0 to 255 so the filter you say has negative values too how is that possible

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please upload quizzz!!!

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[@sourabhsoni2460]

where the filter matrix values came from?

[@mugomuiruri2313]

good

[@user-gu9nw8wy9w]

Sir u took 1and 0 for identification of edges before that u used 0-255pixel number and got output without 0 how it identifies black and white sir

[@lijinhui6902]

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[@CodingLane]

Hehe… welcome!!

[@varikutigangagowri5341]

How to take filter values

[@KomalSingh.87]

Kindly upload the quiz

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can you please upload the quiz

[@gurmeetchauhanfoj3850]

Quiz link please

[@burerabiya7866]

Hello I need you presentation ?could you please share your presentation slides

[@kumpatiasheer1895]

how you will
take the filter values like 1 0 -1..?

[@CodingLane]

You don’t set the filter values manually, but these values are trained using backpropagation. I have explained that in further video. Training the model automatically sets the appropriate filter values necessary to detect features in images (and we may not know what that filter is detecting)

[@kritibhaskar3286]

Where is the quiz

[@parthapratim8369]

Best best best

[@saranyavijayan2149]

How do we choose the filter size ?

[@CodingLane]

If your data has more complicated information, you can take bigger filter size. Otherwise smaller. You will need to test your filter size and number of filters by training the model and checking the accuracy. Take the filter size and no. of filters where you get the highest accuracy.

[@venkatswaraj3054]

Please upload the quiz. Atleast do it in google forms. Thanks in advance.

[@debashishtiu2919]

Research project?

[@astatosiseverywhere]

upload the quiz sir

[@wanderlust0904]

sir there is no quiz please upload it again

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Assignment Quiz?

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where is quiz ?

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quiz pls

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[@ReviewGame10]

Bro forgot :('📕 Sorry, the Assessment quiz was deleted due to a technical issue. I will upload it after some time. '

[@sairam4998]

google form not found for quiz!

[@CodingLane]

Thanks for letting me know. I accidentally deleted it from my drive. I will re-upload it again after some time if I find that quiz.

[@iduzeth5606]

I want that quiz 😭, I am ready

[@oyebamijimicheal8372]

😁😁

[@lochuynh6734]

I think this operator would be Cross Correlation. Did I have any mistake?

[@CodingLane]

Hi Loc. Both Convolution Operation and Cross-correlation operation works the same way. We just use flipped filter values in the one.
But, both can be used to achieve same purpose.
In this video, at 4:44, you can understand the difference: czcams.com/video/tQYZaDn_kSg/video.html

[@CodingLane]

Let me know if you still need some clarity

[@lochuynh6734]

@@CodingLane oh I see, thank you so much.

[@axitamohanta6743]

how it become 4*4 matrix?

[@anythingilike237]

we have n*n size matrix and filter size f*f then we apply formula (n-f+1) * (n-f+1)

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[@CodingLane]

You can mail me at [e-mail]

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Can i connect with you on LinkedIn please

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😢😢😢quiz

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Haha… if you propose

[@patrickorone1149]

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[@CodingLane]

Happy to help 😇

[@neeveshjain]

where is quiz ?