I will talk about the history of Convolutional
Neural Networks, and I call this part of history
as cats and it will become obvious why I call
it so.
So, around 1959 Hubel and Wiesel did this
famous experiment they are still I think you
could see some videos of it on YouTube, where
there is this cat and there was a screen in
front of it and on the screen there were these
lines being displayed at different locations
and in different orientations right.
So, slanted, horizontal, vertical and so on
and there are some electrodes fitted to the
cat and they were measuring trying to measure
that which parts of brain actually respond
to different visual stimuli.
Let us say if you show it stimulus at a certain
location, does the different part of the brain
fire and so on right.
So, and one of the things of outcomes of the
study was that, that different neurons in
brain fire to only different types of stimuli,
it is not that all neurons in brain always
fire to any kind of visual stimuli that you
give to them right.
So, this is essentially roughly the idea behind
convolutional neural networks starting from
something known as Neocognitron, which was
proposed way back in 1980.
You could think of it as a very primitive
convolutional neural network, I am sure that
most of you have now read about or heard about
convolutional neural networks, but something
very similar to it was proposed way back in
1980.
And what we know as the modern convolutional
neural networks maybe I think Yan Li Kun is
someone who proposed them way back in 1989,
and he was interested in using them for the
task of handwritten digit recognition and
this was again in the context of postal delivery
services right.
So, lot of pin codes get written or phone
numbers get written on the postcards and there
was a requirement to read them automatically.
So, that they can be the letters or postcards
can be separated into different categories
according to the postcard according to the
postal code and so on right so or the pin
code.
So, that is where this interest was there
and 1989 was when this convolutional neural
networks were first proposed or used for this
task.
And then over the years, several improvements
were done to that; and in 1998 this now how
famous data set the MNIST data set which is
used for teaching deep neural networks, courses
or even for initial experiments with various
neural network based networks.
This is one of the popular data sets, which
is used in this field and this was again released
way back in 1998 and even today even for my
course I use it for various assignments and
so on.
So, it is interesting that an algorithm which
was inspired by an experiment on cats is,
today used to detect cats in videos of course,
among other various other things is just I
am just jokingly saying this.
