IAPR-TC3
Neural Networks & Computational Intelligence
Manifesto: off-the-mainstream research
"Mainstream science is about publishing what everyone else is publishing
with very small changes. You'd better at least start off that way if you
want to get tenure," the sociologist Rodney Stark said. But "big ideas
don't come to those who avoid risk", as John Bohannon added. The area of
artificial neural networks and machine learning makes no
exception to these ends. Mainstream topics, originally stemming from
exciting breakthroughs (the "big ideas") that gradually become trends and
end-up being mostly over-beaten publishing tracks, have characterized the
scientific literature throughout the whole history of this research
field. Based on these premises, IAPR-TC3 promotes real novel research developments in the areas of neural networks and
learning machines that (1) are rooted in (or, aimed at) pattern
recognition, and that, above all, (2) do not follow in the footsteps
of nowadays established trends.
Established IAPR-TC3 research directions
The main lines of scientific interest to IAPR-TC3 can be grouped as follows:
