# Eyes4ICU Online Seminar Series

## Abstracts

This talk will continue our voyage into the fundamental ideas of Machine Learning that we started in Günzburg. In particular I will move into linear filtering (convolution and correlation). I will try to minimize the amount of mathematics, but this time I must use

- The inner / dot product of vectors (including sums)
- The relation that the inner product of the vectors u and v ( u \dot v) is related to the angle between them

In particular u \dot v = |u||v|cos(theta),

where |u| is the length of the vector u and theta is the angle between u and v.

You can seek a little inspiration here

For those of you who would like to know more about convolution (beyond what I will cover) and have it explained beautifully then have a look here