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Hi,
I often look at AI (esp. CV ones) courses, and, clearly, they are often filled with
lots of equations and other math tools.
I agree that, for example, Vision aims at solving lots of math
problems too, but is it really *necessary* to always knock out grad
students with so many math things?
I never found a document speaking in a more global way about the
problems in Vision. Okay, PhDs and, to a lesser extent, teachers, do
know what they are doing, but think about the grad student who does
not know so many things in CV as the PhD who gives lectures about
it. Is it really the best way to *introduce* a CV course?
- --
Merciadri Luca
See http://www.student.montefiore.ulg.ac.be/~merciadri/
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