Next is Dee Dee Dee 16.
This was the runner up in 2014 a year less VRC challenge.
This was a very big architecture and it had 138 million parameters to be trained so it took a lot of
time to train.
If you look at the architecture instead of convoluted many layers it has conventional blocks and one
block consists of several conventional layers and a max pooling layer at the end to this constitutional
block has to convolution in layers and one Max pooling layer next conditional block has two corners
layers and a max willingly and then we again have a congressional block.
The last two convoluted blocks have three constitutional layers instead of two congressional leaders
after processing up to 20 forward to 24 pixel image.
At the end of all of these convolution layers we had 512 feature maps of 7 by 7 size these feature maps
were fed into a fully connected neural network with so many neurons at the end of it.
There were 1000 output neurons with soft maps activation.
This is because we did see sixteen was run on a problem in which there were 1000 glasses into which
images were to be classified so it was a huge database.
Over a million images and those images were to be classified into one thousand Glasses glasses were
of dog breeds God breeds etc..