Convolution vs Cross Correlation

[LiliumAtratum]

You explained the most direct difference between those two. The more interesting observation is that convolution is associative, while cross-correlation is not. That's why, for example in image processing, convolution is more commonly used.

[travel]

This is not very useful. I watched to understand the intuition behind using these two. But, unfortunately, you only give the information about how to apply the formula on an example. You need to give the intuition behind using these methods (particularly in computer vision) to better understand their differences.

[immortalpuffin]

I think I get it now, so i and j are indices in our kernel, and when we do a summation over the expression using cross correlation / adding the summation counters elements are placed one to one with the original kernel, whereas when you introduce the subtraction of the summation using convolution, the elements are placed in reverse order going from left to right and up to down. Is that right, at least for this example?

[igorcherepanov]

what is the cause for this so-called "flipping"?

[zlzpsnb]

Correlation is Similarity / Convolution is filter
this is my understanding

[OttoFazzl]

I am taking a deep learning course and this was very useful.

[akshatsharma]

I'm bit confused about the Symbols used in this video, Please Help!!!

[jameshopkins]

Are you crazy or what?.Explain something please

[lingfeizhang]

This is one of the worse explanations ive heard in my life