Eyes4ICU Online Seminar Series


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