What are Convolutional Neural Networks (CNNs)?

Рет қаралды 266,634

2 жыл бұрын

Learn more about watsonx → ibm.biz/BdvxDe
Convolutional neural networks, or CNNs, are distinguished from other neural networks by their superior performance with image, speech, or audio signal inputs. But how exactly do they work?
In this lightboard video, Martin Keen with IBM, explains how this deep learning algorithm operates to enable machines to view the world as humans do.
#ConvolutionalNeuralNetworks #Neural Networks #AI

Пікірлер: 109

@sunnygan90 2 жыл бұрын

Unbelievably clear and succinct explanations

@IBMTechnology 2 жыл бұрын

Thanks for the appreciation, Sunny, that's what we strive for! 🙂

@JockGeez 7 ай бұрын

Well said

@AndevOG Жыл бұрын

Explained in a very simple way that's easy to understand! Great video!

@minnaazmy6710 6 күн бұрын

This channel has some of the best CompSci explanations ! Never been disappointed!

@simonrashid-po4zq Ай бұрын

man i like how you clearly explain your videos

@MrMMF94 Жыл бұрын

Such a likeable person explaining so well, much appreciated! :)

@rdbnair1445 2 жыл бұрын

Have been watching several videos to get a high level understanding of CNN, but no luck. However, this is a very good explanation ! Cleared lots of doubt in few minutes. Thank you

@verolthompson502 Ай бұрын

Martin, you are a superb teacher. You make learning easy and fun.

@moonstone6071 4 ай бұрын

Fantastic explanation! Very pedagogical and easy to follow. Thank you!

@vinadiscar5236 2 жыл бұрын

You made it easy to understand. Very helpful. Thanks a lot :)

@nassimaguenaoui3776 Жыл бұрын

Very clear and right-to-the-point explanation! Thank you!

@mohamedvawda979 Жыл бұрын

This explanation was so good. Currently using CNNs for remote sensing applications.

@tjunohambeka1938 Жыл бұрын

This was easy to understand and very concise...Thank you

@jzhao1562 16 сағат бұрын

Fantastic Video. Is Martin always writing mirrored? I am fastinated by how your video recording works!

@arrahul316 2 жыл бұрын

The intro just rocked, as to why CNN. "Humans can do object detection quickly and machines can't" and hence that's where it begins. Amazing... Thanks...

@emc3000 10 ай бұрын

Dear lord this is perfectly chunked information.

@YazanAlManasir Жыл бұрын

thanks martin for the clear explanations you are amazing

@pellythirteen5654 Жыл бұрын

In my eyes , the goal of Convolution is to make the signal invariant to scaling and translation. It acts as a pre-processor of the raw input signal. You could also first pre-process your training set and store it in a file. Then you can use this file and feed it directly to the deep neural network. You don't need the Convolution anymore at training. Another way of making your signal (picture) invariant is to first Fourier Transform it to make it scaling and translation invariant. Next you transform the signal from cartesian to polar coordinates to make it rotational invariant. Finally you Fourier Transform that signal and end up with a fully invariant signal that you can store as a pre-processed Training set.

@sourabhsoni3988 Жыл бұрын

Any citations for elaborating what you said.

@pietjan2409 8 ай бұрын

But CNN makes it possible to sequentially apply more abstract filters that fit the specific objects in the image. I'm not sure if those transformations you named are able to do that, which is taking very complex and abstract patterns into account.

@0xabaki 3 ай бұрын

amazing as usual.

@akmalyafi1470 Жыл бұрын

Hello, thank you for the explanation but I still don't understand how the filters are made.

@jiajunmak4039 2 жыл бұрын

Bro this dude just wrote mirrored wth. Also thanks for the video! The concept of CNN is a lot more clear to me now. :))

@IBMTechnology 2 жыл бұрын

Glad this was useful to you! 👍 As for writing mirrored, here is how we do it 👉 ibm.co/3jnq1st 😉

@Goalkeeper143 Жыл бұрын

Utterly well done, our IBM ML specialist!

@paskalisnani 2 жыл бұрын

Thank you

@JockGeez 7 ай бұрын

This guy gives crystal clear explanations. Supremely Clear!

@elmoreglidingclub3030 Жыл бұрын

Great explanation! Great job; thanks!

@basedmatt Жыл бұрын

What would be the difference between the standard convolutional networks and something newer like CLIP?

@andresinho83 2 жыл бұрын

0:42 I cannot get over the fact that this dude just wrote the term CNN backwards so easily and so fast :O

@andresinho83 2 жыл бұрын

Or maybe he just inverted the video horizontally in post edition

@frankbik1063 2 жыл бұрын

try looking at the video using a mirror ...

@badbud804 9 ай бұрын

He inverted the video. That's why he's writing with his left hand and wearing his clock on the right arm.

@andresinho83 9 ай бұрын

@@badbud804yeah, I also mentioned that but it would be very impressive if he could actually do that

@kitrt 2 жыл бұрын

Hi! Have I assumed correctly that in case of using CNNs for image recognition, the deeper the filters go, the more they zoom out on the image? Next logical question is - what type of software is used to analyze test cases (e.g. real houses) and create those filters?

@ydl6832 Жыл бұрын

The filter is no more than just a matrix. The discrete convolution is performed in each layer (this is where the name CNN comes from). The filter is refined using training data, just like how you would train a perception, you train the matrix to behave as desired.

@kaysonargyle Ай бұрын

Mans just wrote in perfect handwriting BACKWARDS on the glass and no one is talking about it what the heck

@crazymonkey5381 2 жыл бұрын

clearly understandable 🙏🙏🙏

@namadivinodkumar9755 2 жыл бұрын

Can we implement this CNN to determine micro-level profiles, i.e., micrometer level?

@saadat_ic Жыл бұрын

This explanation is good. Thanks. 😊

@bryantea2039 2 жыл бұрын

Well if the beer videos ever stop Martin you have a career in IT Vlogging 😁

@rubenhanjrahing7324 Жыл бұрын

oh my god, thankyou for the explanation. Easy to understand

@kaviarasu.thuraiarasu89 Жыл бұрын

Superb explaination

@user-go4ev8og7k 7 ай бұрын

Explained this video very well - highly recommend! Thank you

@studywithmaike Жыл бұрын

Great video! Thanks 👍🏼

@bran_rx 2 жыл бұрын

this video hits different if you are currently taking digital image processing course. I feel smart lol

@nehaskulkarni 3 ай бұрын

such an easy, clear and to the point explanation! thanks a lot

@ayushmohanty4123 7 ай бұрын

I have a question how are the levels of filters are defined ?

@mzimmerman1988 Ай бұрын

thanks

@constantineyu-yang 3 ай бұрын

So I take the key to building a CNN is on how to build the filters? also, given that the first layer is fragmented, does it mean that the first layer could be of general usage, while the later layers are more application oriented?

@nazrinibrahimli7042 7 ай бұрын

The best explanation ever.

@shunmugapriyamc4522 2 жыл бұрын

Waiting to learn more from you

@biswajitrout4710 2 жыл бұрын

Great content

@monome3038 6 ай бұрын

great work explaining!

@meryamelqamary7638 7 ай бұрын

Hi ,I'm a maths student and I need to do a project. the theme is games and sport. I saw your video and thought why not apply this technique to the world of sports? to discover from the analysis of the players' movements if one is sick. Can you help me to apply CNN and use it well please.

@John-wx3zn Ай бұрын

Don't ask him. His explaination is sloppy and incomplete. The convolution operations with the filters produce matrix channels building the tensor. For example after four convolution operations, you should have four matrix channels. The next operation would be a max pooling operation on each matrix channel in the tensor. Please let me know if you have a question.

@ANIF_CYMBOLIC 23 күн бұрын

Identifying, organizing and reaping to thought. Your tv CAN communicate with you via your neurons producing electromagnetic waves

@rogerfed2030 4 ай бұрын

is this what the vision pro uses?

@user-cz5ne5ik7h 2 жыл бұрын

Thanks a lot!

@austinbao 10 ай бұрын

perfect explanantion. I hate it when people throw difficult terms around. Why can't it be precise and clear such as using a house as an analogy. Well done!

@jimj2683 8 ай бұрын

Doesn't it require a lot of manual work to make all those filters? Isn't it better to just run everything through a regular neural network?

@mubashir22ful 10 ай бұрын

Funny guy. Love him

@jeanpeuplu3862 Жыл бұрын

AWESOME! Thanks :)

@JoaoAssalim 5 ай бұрын

Very good explanation!

@subodhi6 2 жыл бұрын

Thank you..!!

@elenapotapova624 3 ай бұрын

finally ! bravo. clear and concise

@krishnapayneeandy2016 Жыл бұрын

Application of successive Convolutional Filters well presented but at a high level only

@rajhanravi 11 ай бұрын

Wow such a comprehensive content on CNN!

@void1185 5 ай бұрын

amazing work. thank u!

@lordoftherain Жыл бұрын

so by combining the other video of yours. At the end of the the CNN there will be a discriminator which has been trained to know what a house looks like, what an apartment looks like, what a skyscraper looks like and therefore tells you that is a house ?

@praphulshaw2128 7 ай бұрын

What kind of bord do u use to write

@IBMTechnology 7 ай бұрын

See ibm.biz/write-backwards

@albuslee4831 2 ай бұрын

This was so great thank you

@alihankaya9183 11 ай бұрын

Will the Activation Functions video come?

@danyroby8471 Ай бұрын

that was a simple wow,,,,

@IngeniousDimensions369 2 жыл бұрын

More please ☺️☺️

@IBMTechnology 2 жыл бұрын

Definitely what we're planning! 😀 In the meantime, feel free to subscribe to get notified of when we post more videos.

@michaelmcwhirter 2 ай бұрын

Great video 🔥

@chaoukimachreki6422 2 жыл бұрын

This man rocks 🤘

@denissetiawan3645 2 жыл бұрын

Master Inventor. Cool :)

@RaselAhmed-ix5ee 2 жыл бұрын

can you help me regarding my project "human pose estimation"

@IBMTechnology 2 жыл бұрын

Hi Rasel! What sort of help would you need? 🙂

@RaselAhmed-ix5ee 2 жыл бұрын

@@IBMTechnology i have to detect human pose estimation through skeletal data extracted from it

@pierQRzt180 Жыл бұрын

The volume is a bit quiet here.

@alexandre2245 2 жыл бұрын

amazing

@toenytv7946 2 жыл бұрын

👍

@Yewbzee 9 ай бұрын

Machine learning is truly amazing yet it pales into insignificance when compared to the ability of this chap to write backwards.

@capitaopacoca8454 Ай бұрын

I cant tell whether you're joking, but I think the video is flipped horizontally

@DataScienceAI-rf4kx 5 ай бұрын

clear and concise bigger picture of CNN

@MaxXFalcon 8 ай бұрын

It's just like our brain recognises objects. Can we make conscious using this technique? Probably yes in future

@benscott8614 6 ай бұрын

Is he writing backwards...! impressive

@siddharthsinghtanwar2043 3 ай бұрын

No, obviously.

@i_mmm_u 8 ай бұрын

awesome

@carolinefbandeira4493 5 ай бұрын

ily

@MegaMey1234 3 ай бұрын

All I can think of is... that how good he is in writing everything mirrored....

@kozaTG 5 ай бұрын

right into it i like that

@snowykoyuki Жыл бұрын

This is too low level and vague for people who need it and too high level and complicated for children, I believe that you should go more in depth to provide more information such as how the convolution works, different activation methods and different types of layers

@ydl6832 Жыл бұрын

It is just an introduction. If one wants to learn the details, they can search for textbooks, I believe there are countless available.

@aaroncroft7514 5 ай бұрын

Then actually go and study CNNs. This is a brief overview of how they work.

@allenabishek1478 4 ай бұрын

These videos are for 2 demographics, young adults/teenagers who find AI technology fascinating and want to understand how it works. And for children to spark the flame of the scientist inside them towards AI development when they grow up. The Second reason is the most important.

@typingcat Жыл бұрын

Wait, that's a house? I thought it was the head of a tin robot.

@thehappygravedigger Жыл бұрын

Awesome explanations ! ... thank you for sharing your knowledge ;))

@friendssitcom8985 4 ай бұрын

Realising you are a children is good thing

@BatMan__45 Ай бұрын

Wht a explanation

@revertir1 Жыл бұрын

lol u work in garage and u want teach us

@pumbo_nv 10 ай бұрын

Terrible explanation

@John-wx3zn Ай бұрын

Most worst and incomplete explaination and diagrams that I have seen so far for a beginner video. Their is nothing cool about what he did or said. No beginner could do it by this explaination. For example, he said the filters are combined; but they are not combined. Maxpooling is done on the result of the convolution operation only to reduce the size of the image only and this is done only to reduce the number of inputs to the next convolution layer or the inputs to the fully connected neural network for classification.